Package check result: OK Changes to worse in reverse depends: Package: accucor Check: tests New result: ERROR Running ‘testthat.R’ [84s/83s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(accucor) > > test_check("accucor") [ FAIL 14 | WARN 8 | SKIP 0 | PASS 1 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Failure ('test_natural_abundance_correction.R:62:3'): Carbon correction (Excel, simple format) ── `corrected` not equal to `expected_output`. Component "Corrected": Component "A12_1": Mean absolute difference: 92961.3 Component "Corrected": Component "A12_2": Mean absolute difference: 76154.55 Component "Corrected": Component "A12_3": Mean absolute difference: 82701.11 Component "Corrected": Component "D12_1": Mean absolute difference: 65373.33 Component "Corrected": Component "D12_2": Mean absolute difference: 71716.87 Component "Corrected": Component "D12_3": Mean absolute difference: 67593.12 Component "Corrected": Component "R12_1": Mean absolute difference: 111838.8 Component "Corrected": Component "R12_2": Mean absolute difference: 96321.13 Component "Corrected": Component "R12_3": Mean absolute difference: 94132.14 ... ── Failure ('test_natural_abundance_correction.R:124:3'): PoolBeforeDF parameter ── `corrected` not equal to `expected_output`. Component "Corrected": Component "A12_1": Mean absolute difference: 92961.3 Component "Corrected": Component "A12_2": Mean absolute difference: 76154.55 Component "Corrected": Component "A12_3": Mean absolute difference: 82701.11 Component "Corrected": Component "D12_1": Mean absolute difference: 65373.33 Component "Corrected": Component "D12_2": Mean absolute difference: 71716.87 Component "Corrected": Component "D12_3": Mean absolute difference: 67593.12 Component "Corrected": Component "R12_1": Mean absolute difference: 111838.8 Component "Corrected": Component "R12_2": Mean absolute difference: 96321.13 Component "Corrected": Component "R12_3": Mean absolute difference: 94132.14 ... ── Failure ('test_natural_abundance_correction.R:178:3'): Carbon correction (csv, simple format) ── `corrected` not equal to `expected_output`. Component "Corrected": Component "A12_1": Mean absolute difference: 92961.3 Component "Corrected": Component "A12_2": Mean absolute difference: 76154.55 Component "Corrected": Component "A12_3": Mean absolute difference: 82701.11 Component "Corrected": Component "D12_1": Mean absolute difference: 65373.33 Component "Corrected": Component "D12_2": Mean absolute difference: 71716.87 Component "Corrected": Component "D12_3": Mean absolute difference: 67593.12 Component "Corrected": Component "R12_1": Mean absolute difference: 111838.8 Component "Corrected": Component "R12_2": Mean absolute difference: 96321.13 Component "Corrected": Component "R12_3": Mean absolute difference: 94132.14 ... ── Failure ('test_natural_abundance_correction.R:232:3'): Carbon correction (Excel, Classic MAVEN copy/paste) ── `corrected` not equal to `expected_output`. Component "Corrected": Component "A12_1": Mean absolute difference: 92961.3 Component "Corrected": Component "A12_2": Mean absolute difference: 76154.55 Component "Corrected": Component "A12_3": Mean absolute difference: 82701.11 Component "Corrected": Component "D12_1": Mean absolute difference: 65373.33 Component "Corrected": Component "D12_2": Mean absolute difference: 71716.87 Component "Corrected": Component "D12_3": Mean absolute difference: 67593.12 Component "Corrected": Component "R12_1": Mean absolute difference: 111838.8 Component "Corrected": Component "R12_2": Mean absolute difference: 96321.13 Component "Corrected": Component "R12_3": Mean absolute difference: 94132.14 ... ── Failure ('test_natural_abundance_correction.R:285:3'): Deuterium correction (Excel, simple format) ── `corrected` not equal to `expected_output`. Component "Corrected": Component "1_1": Mean absolute difference: 40334.04 Component "Corrected": Component "1_1_": Mean absolute difference: 45035.94 Component "Corrected": Component "1_1_151030015624": Mean absolute difference: 30190.88 Component "Corrected": Component "1_2": Mean absolute difference: 37333.25 Component "Corrected": Component "1_2_": Mean absolute difference: 36700.73 Component "Corrected": Component "1_2_151030022216": Mean absolute difference: 37957.34 Component "Corrected": Component "1D11": Mean absolute difference: 374292.3 Component "Corrected": Component "1D12": Mean absolute difference: 456271.6 Component "Corrected": Component "1D21": Mean absolute difference: 459919.1 ... ── Failure ('test_natural_abundance_correction.R:339:3'): Deuterium correction (Excel, Classic Maven Cut/Paste) ── `corrected` not equal to `expected_output`. Component "Corrected": Component "1_1": Mean absolute difference: 40334.04 Component "Corrected": Component "1_1_": Mean absolute difference: 45035.94 Component "Corrected": Component "1_1_151030015624": Mean absolute difference: 30190.88 Component "Corrected": Component "1_2": Mean absolute difference: 37333.25 Component "Corrected": Component "1_2_": Mean absolute difference: 36700.73 Component "Corrected": Component "1_2_151030022216": Mean absolute difference: 37957.34 Component "Corrected": Component "1D11": Mean absolute difference: 374292.3 Component "Corrected": Component "1D12": Mean absolute difference: 456271.6 Component "Corrected": Component "1D21": Mean absolute difference: 459919.1 ... ── Failure ('test_natural_abundance_correction.R:394:3'): Nitrogen correction (Excel, simple format) ── `corrected` not equal to `expected_output`. Component "Corrected": Component "N15_0_140k_A": Mean absolute difference: 12440408 Component "Corrected": Component "N15_0_140k_B": Mean absolute difference: 14110275 Component "Corrected": Component "N15_0_140k_C": Mean absolute difference: 14684966 Component "Corrected": Component "N15_0_140k_D": Mean absolute difference: 14825838 Component "Corrected": Component "N15_10_140k_A": Mean absolute difference: 9088106 Component "Corrected": Component "N15_10_140k_B": Mean absolute difference: 8804065 Component "Corrected": Component "N15_10_140k_C": Mean absolute difference: 9436492 Component "Corrected": Component "N15_10_140k_D": Mean absolute difference: 9155348 Component "Corrected": Component "N15_50_140k_A": Mean absolute difference: 5782855 ... ── Failure ('test_natural_abundance_correction.R:451:3'): Nitrogen correction (Excel, Classic Maven Cut/Paste) ── `corrected` not equal to `expected_output`. Component "Corrected": Component "N15_0_140k_A": Mean absolute difference: 12440408 Component "Corrected": Component "N15_0_140k_B": Mean absolute difference: 14110275 Component "Corrected": Component "N15_0_140k_C": Mean absolute difference: 14684966 Component "Corrected": Component "N15_0_140k_D": Mean absolute difference: 14825838 Component "Corrected": Component "N15_10_140k_A": Mean absolute difference: 9088106 Component "Corrected": Component "N15_10_140k_B": Mean absolute difference: 8804065 Component "Corrected": Component "N15_10_140k_C": Mean absolute difference: 9436492 Component "Corrected": Component "N15_10_140k_D": Mean absolute difference: 9155348 Component "Corrected": Component "N15_50_140k_A": Mean absolute difference: 5782855 ... ── Failure ('test_natural_abundance_correction.R:509:3'): Carbon correction (csv, El-MAVEN export (with set names)) ── `corrected` not equivalent to `expected_output`. Component "Corrected": Component "blk": Mean absolute difference: 26477.41 Component "Corrected": Component "H-12C-C5-A-20uL": Mean absolute difference: 1508010 Component "Corrected": Component "H-12C-C5-A-40uL": Mean absolute difference: 3835179 Component "Corrected": Component "H-12C-C5-B": Mean absolute difference: 2954252 Component "Corrected": Component "H-12C-N5-A": Mean absolute difference: 1744772 Component "Corrected": Component "H-12C-N5-B": Mean absolute difference: 2599283 Component "Corrected": Component "H-D2O-C44-A": Mean absolute difference: 456342.6 Component "Corrected": Component "H-D2O-C44-B": Mean absolute difference: 647981 Component "Corrected": Component "H-D2O-N44-A": Mean absolute difference: 330469.2 ... ── Failure ('test_natural_abundance_correction.R:564:3'): Carbon correction (Excel, El-MAVEN export (with set names)) ── `corrected` not equal to `expected_output`. Component "Corrected": Component "blk": Mean absolute difference: 26477.41 Component "Corrected": Component "H-12C-C5-A-20uL": Mean absolute difference: 1508010 Component "Corrected": Component "H-12C-C5-A-40uL": Mean absolute difference: 3835179 Component "Corrected": Component "H-12C-C5-B": Mean absolute difference: 2954252 Component "Corrected": Component "H-12C-N5-A": Mean absolute difference: 1744772 Component "Corrected": Component "H-12C-N5-B": Mean absolute difference: 2599283 Component "Corrected": Component "H-D2O-C44-A": Mean absolute difference: 456342.6 Component "Corrected": Component "H-D2O-C44-B": Mean absolute difference: 647981 Component "Corrected": Component "H-D2O-N44-A": Mean absolute difference: 330469.2 ... ── Failure ('test_natural_abundance_correction.R:617:3'): Carbon correction (csv, El-MAVEN export (w/o names)) ── `corrected` not equal to `expected_output`. Component "Corrected": Component "TIGAR_3": Mean absolute difference: 3533.888 Component "Corrected": Component "TIGAR_2": Mean absolute difference: 4025.744 Component "Corrected": Component "TIGAR_1_180419223055": Mean absolute difference: 4232.064 Component "Corrected": Component "TIGAR_1": Mean absolute difference: 4123.572 Component "Normalized": Component "TIGAR_3": 'is.NA' value mismatch: 0 in current 5 in target Component "Normalized": Component "TIGAR_2": 'is.NA' value mismatch: 0 in current 5 in target Component "Normalized": Component "TIGAR_1_180419223055": 'is.NA' value mismatch: 0 in current 5 in target Component "Normalized": Component "TIGAR_1": 'is.NA' value mismatch: 0 in current 5 in target Component "PoolAfterDF": Component "TIGAR_3": Mean absolute difference: 10601.66 ... ── Failure ('test_natural_abundance_correction.R:670:3'): Carbon correction (csv, El-MAVEN, multiple groups per compound) ── `corrected` not equal to `expected_output`. Component "Corrected": Component "blk": Mean absolute difference: 8142.161 Component "Corrected": Component "H-Glc-G6PD-1": Mean absolute difference: 4094958 Component "Corrected": Component "H-Glc-G6PD-2": Mean absolute difference: 4257742 Component "Corrected": Component "H-Glc-G6PD-3": Mean absolute difference: 5691626 Component "Corrected": Component "H-Glc-IDH1-1": Mean absolute difference: 2185385 Component "Corrected": Component "H-Glc-IDH1-2": Mean absolute difference: 2061288 Component "Corrected": Component "H-Glc-IDH1-3": Mean absolute difference: 1934416 Component "Corrected": Component "H-Glc-ME1-1": Mean absolute difference: 3006353 Component "Corrected": Component "H-Glc-ME1-2": Mean absolute difference: 2637176 ... ── Failure ('test_natural_abundance_correction.R:726:3'): Carbon correction (dataframe) ── `corrected` not equal to `expected_output`. Component "Corrected": Component "A12_1": Mean absolute difference: 92961.3 Component "Corrected": Component "A12_2": Mean absolute difference: 76154.55 Component "Corrected": Component "A12_3": Mean absolute difference: 82701.11 Component "Corrected": Component "D12_1": Mean absolute difference: 65373.33 Component "Corrected": Component "D12_2": Mean absolute difference: 71716.87 Component "Corrected": Component "D12_3": Mean absolute difference: 67593.12 Component "Corrected": Component "R12_1": Mean absolute difference: 111838.8 Component "Corrected": Component "R12_2": Mean absolute difference: 96321.13 Component "Corrected": Component "R12_3": Mean absolute difference: 94132.14 ... ── Failure ('test_natural_abundance_correction.R:779:3'): Carbon correction (El-Maven v0.11.0) ── `corrected` not equal to `expected_output`. Component "Corrected": Component "000a_20201117_SRJ_HILICnegpos_0a_0_Blank_0_0_0": Mean absolute difference: 54417.04 Component "Corrected": Component "001_20201117_SRJ_HILICnegpos_1_SL01_P1_24hr_Vehicle_13CGln": Mean absolute difference: 11644944 Component "Corrected": Component "002_20201117_SRJ_HILICnegpos_2_SL02_P1_24hr_Vehicle_13CGln": Mean absolute difference: 11537528 Component "Corrected": Component "003_20201117_SRJ_HILICnegpos_3_SL03_P1_24hr_Vehicle_13CGln": Mean absolute difference: 11668027 Component "Corrected": Component "004_20201117_SRJ_HILICnegpos_4_SL04_P1_24hr_0p5um_13CGln": Mean absolute difference: 11545122 Component "Corrected": Component "005_20201117_SRJ_HILICnegpos_5_SL05_P1_24hr_0p5um_13CGln": Mean absolute difference: 13075103 Component "Corrected": Component "006_20201117_SRJ_HILICnegpos_6_SL06_P1_24hr_0p5um_13CGln": Mean absolute difference: 11167071 Component "Corrected": Component "007_20201117_SRJ_HILICnegpos_7_SL07_P1_24hr_1um_13CGln": Mean absolute difference: 14323363 Component "Corrected": Component "008_20201117_SRJ_HILICnegpos_8_SL08_P1_24hr_1um_13CGln": Mean absolute difference: 11817296 ... [ FAIL 14 | WARN 8 | SKIP 0 | PASS 1 ] Error: Test failures Execution halted Package: adamethods Check: examples New result: ERROR Running examples in ‘adamethods-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: archetypoids_norm_frob > ### Title: Archetypoid algorithm with the Frobenius norm > ### Aliases: archetypoids_norm_frob > > ### ** Examples > > data(mtcars) > data <- mtcars > > k <- 3 > numRep <- 2 > huge <- 200 > > lass <- stepArchetypesRawData_norm_frob(data = data, numArch = k, + numRep = numRep, verbose = FALSE) Warning in archetypes_norm_frob(data, k = numArch[i], saveHistory = FALSE, : k=3: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes_norm_frob(data, k = numArch[i], saveHistory = FALSE, : k=3: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve > > res <- archetypoids_norm_frob(k, data, huge, ArchObj = lass) Error in archetypoids_norm_frob(k, data, huge, ArchObj = lass) : No archetypes computed Execution halted Package: Anthropometry Check: examples New result: ERROR Running examples in ‘Anthropometry-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: archetypesBoundary > ### Title: Archetypal analysis in multivariate accommodation problem > ### Aliases: archetypesBoundary > ### Keywords: array > > ### ** Examples > > #The following R code allows us to reproduce the results of the paper Epifanio et al. (2013). > #As a toy example, only the first 25 individuals are used. > #First,the USAF 1967 database is read and preprocessed (Zehner et al. (1993)). > #Variable selection: > variabl_sel <- c(48, 40, 39, 33, 34, 36) > #Changing to inches: > USAFSurvey_inch <- USAFSurvey[1:25, variabl_sel] / (10 * 2.54) > > #Data preprocessing: > USAFSurvey_preproc <- preprocessing(USAFSurvey_inch, TRUE, 0.95, TRUE) [1] "The percentage of accommodation is exactly 100%" > > #Procedure and results shown in section 2.2.2 and section 3.1: > #For reproducing results, seed for randomness: > #suppressWarnings(RNGversion("3.5.0")) > #set.seed(2010) > res <- archetypesBoundary(USAFSurvey_preproc$data, 15, FALSE, 3) Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=1: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=1: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=1: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=2: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=2: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=2: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=3: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=3: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=3: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=4: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=4: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=4: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=5: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=5: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=5: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=6: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=6: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=6: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=7: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=7: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=7: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=8: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=8: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=8: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=9: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=9: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=9: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=10: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=10: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=10: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=11: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=11: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=11: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=12: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=12: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=12: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=13: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=13: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=13: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=14: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=14: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=14: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=15: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=15: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in archetypes(data, k = numArch[i], family = archetypesFamily("original", : k=15: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve > #To understand the warning messages, see the vignette of the > #archetypes package. > > #Results shown in section 3.2 (figure 3): > screeplot(res) Warning in min(x) : no non-missing arguments to min; returning Inf Warning in max(x) : no non-missing arguments to max; returning -Inf Error in plot.window(...) : need finite 'ylim' values Calls: screeplot ... screeplot.stepArchetypes -> plot -> plot.default -> localWindow -> plot.window Execution halted Package: archetypes Check: examples New result: ERROR Running examples in ‘archetypes-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: simplexplot > ### Title: Simplex visualization > ### Aliases: simplexplot > > ### ** Examples > > ### This example reproduces parts of the Figure 7 shown in > ### "Probabilistic Archetypal Analysis" by Seth and Eugster (2014) > > data("toy", package = "archetypes") > > suppressWarnings(RNGversion("3.5.0")) > set.seed(1234); a3 <- archetypes(toy, k = 3) Warning in archetypes(toy, k = 3) : k=3: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve > set.seed(1237); a4 <- archetypes(toy, k = 4) Warning in archetypes(toy, k = 4) : k=4: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve > set.seed(1238); a5 <- archetypes(toy, k = 5) Warning in archetypes(toy, k = 5) : k=5: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve > > simplexplot(a3) Error in rep(points_col, nrow(coef(object))) : invalid 'times' argument Calls: simplexplot Execution halted Package: archetypes Check: re-building of vignette outputs New result: ERROR Error(s) in re-building vignettes: ... --- re-building ‘archetypes.Rnw’ using Sweave Loading required package: modeltools Loading required package: stats4 Loading required package: nnls Warning in archetypes(toy, 3, verbose = TRUE) : k=3: Error in qr.solve(alphas %*% t(alphas)): singular matrix 'a' in solve Warning in mean.default(xc) : argument is not numeric or logical: returning NA Warning in mean.default(yc) : argument is not numeric or logical: returning NA Warning in mean.default(xc) : argument is not numeric or logical: returning NA Warning in mean.default(yc) : argument is not numeric or logical: returning NA Error: processing vignette 'archetypes.Rnw' failed with diagnostics: chunk 9 Error in t.default(object$archetypes) : argument is not a matrix --- failed re-building ‘archetypes.Rnw’ SUMMARY: processing the following file failed: ‘archetypes.Rnw’ Error: Vignette re-building failed. Execution halted Package: bnpsd Check: tests New result: ERROR Running ‘testthat.R’ [6s/6s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(bnpsd) > > test_check('bnpsd') [ FAIL 10 | WARN 0 | SKIP 0 | PASS 908 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Failure ('test_bnpsd.R:2446:5'): fit_tree_single works ────────────────────── tree_fit$rss not equal to 0. 1/1 mismatches [1] 25.2 - 0 == 25.2 ── Failure ('test_bnpsd.R:2449:5'): fit_tree_single works ────────────────────── `tree_fit` not equal to `tree`. FALSE ── Failure ('test_bnpsd.R:2461:5'): fit_tree_single works ────────────────────── tree_rand_fit$rss not equal to 0. 1/1 mismatches [1] 25.2 - 0 == 25.2 ── Failure ('test_bnpsd.R:2463:5'): fit_tree_single works ────────────────────── `tree_rand_fit` not equal to `tree_rand`. FALSE ── Failure ('test_bnpsd.R:2486:5'): fit_tree_single works ────────────────────── tree_fit$rss not equal to 0. 1/1 mismatches [1] 25.2 - 0 == 25.2 ── Failure ('test_bnpsd.R:2488:5'): fit_tree_single works ────────────────────── `tree_fit` not equal to `tree`. FALSE ── Failure ('test_bnpsd.R:2529:5'): fit_tree works ───────────────────────────── tree_fit$rss not equal to 0. 1/1 mismatches [1] 4.36 - 0 == 4.36 ── Failure ('test_bnpsd.R:2532:5'): fit_tree works ───────────────────────────── `tree_fit` not equal to `tree`. FALSE ── Failure ('test_bnpsd.R:2543:5'): fit_tree works ───────────────────────────── tree_fit$rss not equal to 0. 1/1 mismatches [1] 4.36 - 0 == 4.36 ── Failure ('test_bnpsd.R:2545:5'): fit_tree works ───────────────────────────── `tree_fit` not equal to `tree`. FALSE [ FAIL 10 | WARN 0 | SKIP 0 | PASS 908 ] Error: Test failures Execution halted Package: ddml Check: tests New result: ERROR Running ‘testthat.R’ [33s/32s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(ddml) > > test_check("ddml") sample fold 1/3 sample fold 2/3 sample fold 3/3[ FAIL 6 | WARN 0 | SKIP 0 | PASS 130 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test-ddml_fpliv.R:11:3'): ddml_fpliv computes with a single model ─── Error in `predict.ensemble(mdl_fit, newdata = X[subsamples[[k]], , drop = F], newZ = Z[subsamples[[k]], , drop = F])`: object 'fitted_mat' not found Backtrace: ▆ 1. └─ddml::ddml_fpliv(y, D, Z, X, learners, sample_folds = 3, silent = T) at test-ddml_fpliv.R:11:3 2. └─ddml:::get_CEF(...) 3. └─ddml::crosspred(...) 4. └─ddml:::predict.ensemble(...) ── Error ('test-ddml_fpliv.R:35:3'): ddml_fpliv computes with a single model and dependence ── Error in `predict.ensemble(mdl_fit, newdata = X[subsamples[[k]], , drop = F], newZ = Z[subsamples[[k]], , drop = F])`: object 'fitted_mat' not found Backtrace: ▆ 1. └─ddml::ddml_fpliv(...) at test-ddml_fpliv.R:35:3 2. └─ddml:::get_CEF(...) 3. └─ddml::crosspred(...) 4. └─ddml:::predict.ensemble(...) ── Error ('test-ddml_fpliv.R:101:3'): ddml_fpliv computes with multiple ensemble procedures ── Error in `predict.ensemble(mdl_fit, newdata = X[subsamples[[k]], , drop = F], newZ = Z[subsamples[[k]], , drop = F])`: object 'fitted_mat' not found Backtrace: ▆ 1. └─ddml::ddml_fpliv(...) at test-ddml_fpliv.R:101:3 2. └─ddml:::get_CEF(...) 3. └─ddml::crosspred(...) 4. └─ddml:::predict.ensemble(...) ── Error ('test-ddml_fpliv.R:173:3'): ddml_fpliv computes with multiple ensembles and sparse matrices ── Error in `predict.ensemble(mdl_fit, newdata = X[subsamples[[k]], , drop = F], newZ = Z[subsamples[[k]], , drop = F])`: object 'fitted_mat' not found Backtrace: ▆ 1. └─ddml::ddml_fpliv(...) at test-ddml_fpliv.R:173:3 2. └─ddml:::get_CEF(...) 3. └─ddml::crosspred(...) 4. └─ddml:::predict.ensemble(...) ── Error ('test-ddml_fpliv.R:203:3'): ddml_fpliv computes with different sets of learners ── Error in `predict.ensemble(mdl_fit, newdata = X[subsamples[[k]], , drop = F], newZ = Z[subsamples[[k]], , drop = F])`: object 'fitted_mat' not found Backtrace: ▆ 1. └─ddml::ddml_fpliv(...) at test-ddml_fpliv.R:203:3 2. └─ddml:::get_CEF(...) 3. └─ddml::crosspred(...) 4. └─ddml:::predict.ensemble(...) ── Error ('test-ddml_fpliv.R:344:3'): ddml_fpliv computes with multiple ensemble procedures, multi D ── Error in `predict.ensemble(mdl_fit, newdata = X[subsamples[[k]], , drop = F], newZ = Z[subsamples[[k]], , drop = F])`: object 'fitted_mat' not found Backtrace: ▆ 1. └─ddml::ddml_fpliv(...) at test-ddml_fpliv.R:344:3 2. └─ddml:::get_CEF(...) 3. └─ddml::crosspred(...) 4. └─ddml:::predict.ensemble(...) [ FAIL 6 | WARN 0 | SKIP 0 | PASS 130 ] Error: Test failures Execution halted Package: drpop Check: tests New result: ERROR Running ‘testthat.R’ [54s/51s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(drpop) > > test_check("drpop") # weights: 9 (4 variable) initial value 800.888358 final value 678.496877 converged # weights: 9 (4 variable) initial value 800.888358 final value 696.515226 converged # weights: 9 (4 variable) initial value 800.888358 final value 692.776589 converged # weights: 9 (4 variable) initial value 800.888358 final value 685.078304 converged # weights: 9 (4 variable) initial value 804.184195 final value 691.978674 converged # weights: 15 (8 variable) initial value 770.127214 iter 10 value 640.454598 final value 639.636053 converged # weights: 15 (8 variable) initial value 770.127214 iter 10 value 617.028361 final value 615.913260 converged # weights: 15 (8 variable) initial value 770.127214 iter 10 value 635.970460 final value 635.094989 converged # weights: 15 (8 variable) initial value 770.127214 iter 10 value 625.101853 final value 624.627551 converged # weights: 15 (8 variable) initial value 773.423051 iter 10 value 643.093145 final value 642.496682 converged [ FAIL 1 | WARN 2 | SKIP 0 | PASS 7 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('testdrpop.R:43:1'): (code run outside of `test_that()`) ───────────── Error in `mod1$coefficients`: $ operator is invalid for atomic vectors Backtrace: ▆ 1. └─drpop::popsize(data = data) at testdrpop.R:43:1 2. └─drpop:::popsize_base(...) 3. └─drpop::tmle(datmat = datmat, margin = margin, K = K, ...) [ FAIL 1 | WARN 2 | SKIP 0 | PASS 7 ] Error: Test failures Execution halted Package: GeoFIS Check: re-building of vignette outputs New result: ERROR Error(s) in re-building vignettes: ... --- re-building ‘data-fusion.Rmd’ using rmarkdown Quitting from lines 287-289 [unnamed-chunk-20] (data-fusion.Rmd) Error: processing vignette 'data-fusion.Rmd' failed with diagnostics: invalid 'n' - must contain at least one non-missing element, got none. --- failed re-building ‘data-fusion.Rmd’ --- re-building ‘zoning.html.asis’ using asis --- finished re-building ‘zoning.html.asis’ SUMMARY: processing the following file failed: ‘data-fusion.Rmd’ Error: Vignette re-building failed. Execution halted Package: GeoFIS Check: tests New result: ERROR Running ‘testthat.R’ [5s/5s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(GeoFIS) Loading required package: sp Loading required package: data.tree Loading required package: FisPro > > test_check("GeoFIS") Linking to GEOS 3.13.0, GDAL 3.9.2, PROJ 9.5.0; sf_use_s2() is TRUE [ FAIL 5 | WARN 0 | SKIP 28 | PASS 177 ] ══ Skipped tests (28) ══════════════════════════════════════════════════════════ • Skipping fusion test (13): 'test_aggreg_fis.R:4:3', 'test_aggreg_fis.R:42:3', 'test_fis_fusion.R:4:3', 'test_fis_fusion.R:25:3', 'test_fis_fusion.R:33:3', 'test_fis_fusion.R:38:3', 'test_fis_fusion.R:46:3', 'test_fis_fusion.R:84:3', 'test_fis_fusion.R:100:3', 'test_fis_fusion.R:127:3', 'test_fis_fusion.R:145:3', 'test_fusion_tolima.R:91:3', 'test_fusion_tolima.R:100:3' • Skipping zoning test (15): 'test_data_in_zone.R:61:3', 'test_data_in_zone.R:75:3', 'test_zoning.R:80:3', 'test_zoning.R:88:3', 'test_zoning.R:109:3', 'test_zoning.R:115:3', 'test_zoning.R:125:3', 'test_zoning.R:138:3', 'test_zoning.R:145:3', 'test_zoning.R:155:3', 'test_zoning.R:169:3', 'test_zoning.R:187:3', 'test_zoning.R:206:3', 'test_zoning.R:227:3', 'test_zoning.R:248:3' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test_learning.R:36:3'): WAM learning weights ──────────────────────── Error in `tail.default(order(x - y), up - sum(y))`: invalid 'n' - must contain at least one non-missing element, got none. Backtrace: ▆ 1. └─GeoFIS::LearnWamWeights(get_data(), target, 4) at test_learning.R:36:3 2. └─GeoFIS:::.get_rounded_weights(weights, digits) 3. ├─utils::tail(order(x - y), up - sum(y)) 4. └─utils:::tail.default(order(x - y), up - sum(y)) 5. └─utils::.checkHT(n, dx <- dim(x)) ── Error ('test_learning.R:44:3'): OWA learning weights ──────────────────────── Error in `tail.default(order(x - y), up - sum(y))`: invalid 'n' - must contain at least one non-missing element, got none. Backtrace: ▆ 1. └─GeoFIS::LearnOwaWeights(get_data(), target, 4) at test_learning.R:44:3 2. └─GeoFIS:::.get_rounded_weights(weights, digits) 3. ├─utils::tail(order(x - y), up - sum(y)) 4. └─utils:::tail.default(order(x - y), up - sum(y)) 5. └─utils::.checkHT(n, dx <- dim(x)) ── Error ('test_learning_cars.R:14:3'): Cars weights ─────────────────────────── Error in `tail.default(order(x - y), up - sum(y))`: invalid 'n' - must contain at least one non-missing element, got none. Backtrace: ▆ 1. └─GeoFIS::LearnWamWeights(degrees, target) at test_learning_cars.R:14:3 2. └─GeoFIS:::.get_rounded_weights(weights, digits) 3. ├─utils::tail(order(x - y), up - sum(y)) 4. └─utils:::tail.default(order(x - y), up - sum(y)) 5. └─utils::.checkHT(n, dx <- dim(x)) ── Error ('test_learning_chaparral.R:8:3'): Chaparral WAM learning weights ───── Error in `tail.default(order(x - y), up - sum(y))`: invalid 'n' - must contain at least one non-missing element, got none. Backtrace: ▆ 1. └─GeoFIS::LearnWamWeights(chaparral_data, chaparral_target) at test_learning_chaparral.R:8:3 2. └─GeoFIS:::.get_rounded_weights(weights, digits) 3. ├─utils::tail(order(x - y), up - sum(y)) 4. └─utils:::tail.default(order(x - y), up - sum(y)) 5. └─utils::.checkHT(n, dx <- dim(x)) ── Error ('test_learning_chaparral.R:17:3'): Chaparral OWA learning weights ──── Error in `tail.default(order(x - y), up - sum(y))`: invalid 'n' - must contain at least one non-missing element, got none. Backtrace: ▆ 1. └─GeoFIS::LearnOwaWeights(chaparral_data, chaparral_target) at test_learning_chaparral.R:17:3 2. └─GeoFIS:::.get_rounded_weights(weights, digits) 3. ├─utils::tail(order(x - y), up - sum(y)) 4. └─utils:::tail.default(order(x - y), up - sum(y)) 5. └─utils::.checkHT(n, dx <- dim(x)) [ FAIL 5 | WARN 0 | SKIP 28 | PASS 177 ] Error: Test failures Execution halted Package: hNMF Check: examples New result: ERROR Running examples in ‘hNMF-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: hNMF > ### Title: Hierarchical non-negative matrix factorization. > ### Aliases: hNMF > > ### ** Examples > > > # create nmfInput object > X <- matrix(runif(10*20), 10,20) > bgImageTensor <- array(0,dim=dim(X)) > selectVect <- array(1,dim=dim(X)) > nmfInput <- NULL > nmfInput$numRows <- nrow(X) > nmfInput$numCols <- ncol(X) > nmfInput$numSlices <- 1 > nmfInput$bgImageTensor <- bgImageTensor > nmfInput$selectVect <- selectVect > > # run NMF with default algorithm, 5 runs with random initialization > NMFresult1 <- oneLevelNMF(X, rank=2, nruns=5) [1] "Init gradient norm: 12.5474546229885" [1] "Relative error: 0.00201648182713116 after 10 iterations" [1] "Relative error: 5.93159303894275e-05 after 20 iterations" [1] "Init gradient norm: 9.81822974581674" [1] "Relative error: 0.000375537576507513 after 10 iterations" [1] "Relative error: 9.69726826413915e-06 after 20 iterations" [1] "Init gradient norm: 14.970902402454" [1] "Relative error: 0.0026646092387565 after 10 iterations" [1] "Relative error: 0.0002060861640702 after 20 iterations" [1] "Relative error: 2.20003886479455e-05 after 30 iterations" [1] "Init gradient norm: 18.6969954625444" [1] "Relative error: 0.00241644717307701 after 10 iterations" [1] "Relative error: 0.000101482596492776 after 20 iterations" [1] "Relative error: 2.26312985622478e-05 after 30 iterations" [1] "Init gradient norm: 14.110872658221" [1] "Relative error: 0.00250669830330755 after 10 iterations" [1] "Relative error: 0.000113243569882177 after 20 iterations" [1] "Relative error: 1.31678688527131e-05 after 30 iterations" > > # run NMF with specified algorithm and with initialized sources > W0 <- initializeSPA(X,3) Warning in U[, j] * (t(U[, j]) %*% U[, iter]) : Recycling array of length 1 in vector-array arithmetic is deprecated. Use c() or as.vector() instead. Warning in (t(v) %*% U[, j]) * U[, j] : Recycling array of length 1 in array-vector arithmetic is deprecated. Use c() or as.vector() instead. Warning in U[, j] * (t(U[, j]) %*% U[, iter]) : Recycling array of length 1 in vector-array arithmetic is deprecated. Use c() or as.vector() instead. Warning in U[, j] * (t(U[, j]) %*% U[, iter]) : Recycling array of length 1 in vector-array arithmetic is deprecated. Use c() or as.vector() instead. Warning in (t(v) %*% U[, j]) * U[, j] : Recycling array of length 1 in array-vector arithmetic is deprecated. Use c() or as.vector() instead. Warning in (t(v) %*% U[, j]) * U[, j] : Recycling array of length 1 in array-vector arithmetic is deprecated. Use c() or as.vector() instead. > NMFresult2 <- oneLevelNMF(X, rank=3, method="HALSacc", initData = W0) Error in while (eps > sqrt(delta) * eps0) { : missing value where TRUE/FALSE needed Calls: oneLevelNMF -> HALSacc -> HALSupdt Execution halted Package: ltmle Check: tests New result: ERROR Running ‘testthat.R’ [21s/21s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(ltmle) > > test_check("ltmle") seed set to 1 Estimator: tmle Estimate Std. Error CI 2.5% CI 97.5% p-value (Intercept) -3.5478 NA NA NA NA time 0.5402 NA NA NA NA switch.time NA NA NA NA NA deterministic.g.function is inconsistent with data. After setting Anodes to abar, the data looks like this: W A1 A2 Y 1 -1.2756187 0 1 0 2 0.7629063 0 1 0 3 -0.4068151 0 1 1 4 -1.2083178 0 1 0 5 -0.4393227 0 1 1 6 -0.3755807 0 1 1 Estimator: tmle Call: ltmle(data = data, Anodes = "A", Ynodes = "Y", abar = 1, gbounds = c(0, 1), estimate.time = FALSE) Parameter Estimate: 0.64904 Estimated Std Err: 16775 p-value: 0.99997 95% Conf Interval: (0, 1) Error in solve.default(a) : Lapack routine dgesv: system is exactly singular: U[2,2] = 0 Error in solve.default(a, b) : Lapack routine dgesv: system is exactly singular: U[2,2] = 0 Call: ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y", abar = 1, estimate.time = F) TMLE Estimate: 0.770777 Estimator: tmle Call: ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y", abar = 1, estimate.time = F) Parameter Estimate: 0.77078 Estimated Std Err: 0.12749 p-value: 1.405e-06 95% Conf Interval: (0.51003, 1) Call: ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y", abar = list(1, 0), estimate.time = F) Use summary(...) to get estimates, standard errors, p-values, and confidence intervals for treatment EYd, control EYd, additive effect, relative risk, and odds ratio. Estimator: tmle Call: ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y", abar = list(1, 0), estimate.time = F) Treatment Estimate: Parameter Estimate: 0.77078 Estimated Std Err: 0.12749 p-value: 1.405e-06 95% Conf Interval: (0.51003, 1) Control Estimate: Parameter Estimate: 0.53582 Estimated Std Err: 0.12121 p-value: 0.00012644 95% Conf Interval: (0.28792, 0.78373) Additive Treatment Effect: Parameter Estimate: 0.23496 Estimated Std Err: 0.17519 p-value: 0.19029 95% Conf Interval: (-0.12335, 0.59326) Relative Risk: Parameter Estimate: 1.4385 Est Std Err log(RR): 0.27947 p-value: 0.2035 95% Conf Interval: (0.81221, 2.5477) Odds Ratio: Parameter Estimate: 2.913 Est Std Err log(OR): 0.86607 p-value: 0.22692 95% Conf Interval: (0.49552, 17.124) Call: ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y", abar = 1, estimate.time = F) TMLE Estimate: 0.770777 Estimator: tmle Call: ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y", abar = 1, estimate.time = F) Parameter Estimate: 0.77078 Estimated Std Err: 0.12749 p-value: 1.405e-06 95% Conf Interval: (0.51003, 1) Call: ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y", abar = list(1, 0), estimate.time = F) Use summary(...) to get estimates, standard errors, p-values, and confidence intervals for treatment EYd, control EYd, additive effect, relative risk, and odds ratio. Estimator: tmle Call: ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y", abar = list(1, 0), estimate.time = F) Treatment Estimate: Parameter Estimate: 0.77078 Estimated Std Err: 0.12749 p-value: 1.405e-06 95% Conf Interval: (0.51003, 1) Control Estimate: Parameter Estimate: 0.53582 Estimated Std Err: 0.12121 p-value: 0.00012644 95% Conf Interval: (0.28792, 0.78373) Additive Treatment Effect: Parameter Estimate: 0.23496 Estimated Std Err: 0.17519 p-value: 0.19029 95% Conf Interval: (-0.12335, 0.59326) Relative Risk: Parameter Estimate: 1.4385 Est Std Err log(RR): 0.27947 p-value: 0.2035 95% Conf Interval: (0.81221, 2.5477) Odds Ratio: Parameter Estimate: 2.913 Est Std Err log(OR): 0.86607 p-value: 0.22692 95% Conf Interval: (0.49552, 17.124) Call: ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y", abar = 1, estimate.time = F, gcomp = T) GCOMP Estimate: 0.7297694 Estimator: gcomp Warning: inference for gcomp is not accurate! It is based on TMLE influence curves. Call: ltmle(data = data.frame(W, A, Y), Anodes = "A", Ynodes = "Y", abar = 1, estimate.time = F, gcomp = T) Parameter Estimate: 0.72977 Estimated Std Err: 0.13033 p-value: 4.8028e-06 95% Conf Interval: (0.46322, 0.99632) [ FAIL 1 | WARN 161 | SKIP 6 | PASS 166 ] ══ Skipped tests (6) ═══════════════════════════════════════════════════════════ • On CRAN (4): 'test-(init).R:5:3', 'test-EstimateVariance.R:4:3', 'test-Weights.R:73:3', 'test-random.R:7:3' • empty test (2): 'test-AbarAndRegimes.R:84:1', 'test-print.R:3:1' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Failure ('test-CheckInputs.R:136:3'): cvControl requires correct names and makes a difference ── abs(r1$estimates["tmle"] - r2$estimates["tmle"]) is not strictly more than 0.001. Difference: -0.001 [ FAIL 1 | WARN 161 | SKIP 6 | PASS 166 ] Error: Test failures Execution halted Package: miscIC Check: examples New result: ERROR Running examples in ‘miscIC-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: miscIC > ### Title: Nonparametric Maximum Likelihood Estimation of the survivor > ### function for interval censored time-to-event data > ### Aliases: miscIC > ### Keywords: survival nonparametric models > > ### ** Examples > > ### Analysis of the example dataset > ### Fixed error probabilities > fit_fixed <- miscIC(state~time,data=simulated_data,subject=subject,initial=c(0.05,0.1),est.e=FALSE) Error in if (max(DD) < 1e-08) conv <- TRUE : missing value where TRUE/FALSE needed Calls: miscIC -> miscICfitting -> computeF_gen Execution halted Package: nlsic Check: examples New result: ERROR Running examples in ‘nlsic-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: nlsic > ### Title: Non Linear Least Squares with Inequality Constraints > ### Aliases: nlsic > > ### ** Examples > > # solve min_{a,b} ||exp(a*x+b)-meas||, a,b>=1 > a_true=1; b_true=2; x=0:5 > # simulation function > sim=function(par, x) exp(par[["a"]]*x+par[["b"]]) > # residual function to be passed to nlsic() > resid=function(par, cjac, ...) { + dots=list(...) + s=sim(par, dots$x) + result=list(res=s-dots$meas) + if (cjac) { + result$jacobian=cbind(a=s*dots$x, b=s) + } + result + } > # simulated noised measurements for true parameters > set.seed(7) # for reproducible results > meas=sim(c(a=a_true, b=b_true), x)+rnorm(x) > # starting values for par > par=c(a=0, b=0) > # prepare constraints > uco=uplo2uco(par, lower=c(a=1, b=1)) > # main call: solve the problem > fit=nlsic(par, resid, uco$u, uco$co, control=list(trace=1), x=x, meas=meas) > if (fit$error == 1) { + stop(fit$mes) + } else { + print(fit$par) # a=1.001590, b=1.991194 + if (! is.null(fit$mes)) { + warning(fit$mes) + } + } Error: nlsic: Unfeasible constraints at starting point (u%*%par-co>0): a >= 1 (-1) b >= 1 (-1) Execution halted Package: nlsic Check: tests New result: ERROR Running ‘RUnit.R’ [0s/0s] Running the tests in ‘tests/RUnit.R’ failed. Complete output: > if (requireNamespace("RUnit", quietly=TRUE)) { + library(RUnit) + library(nlsic) + + testSuite <- defineTestSuite( + name = "nlsic unit tests", + dirs = system.file("unitTests", package = "nlsic"), + testFuncRegexp = "^[Tt]est.+" + ) + Sys.setenv("R_TESTS"="") + tests <- runTestSuite(testSuite) + + printTextProtocol(tests) + err=getErrors(tests) + if (err$nFail > 0) stop("RUnit: ", err$nFail, " test failure(s)") + if (err$nErr > 0) stop("RUnit: ", err$nErr, " error(s) in RUnit tests") + } Loading required package: nnls Executing test function test.Nulla ... done successfully. Executing test function test.join ... done successfully. Executing test function test.ldp ... Timing stopped at: 0.002 0.001 0.001 Error in checkEqualsNumeric(x, c(1, 0, 0)) : Modes: NULL, numeric Lengths: 0, 3 target is NULL, current is numeric In addition: Warning messages: 1: In RNGkind(kind = testSuite$rngKind, normal.kind = testSuite$rngNormalKind) : RNGkind: Marsaglia-Multicarry has poor statistical properties 2: In RNGkind(kind = testSuite$rngKind, normal.kind = testSuite$rngNormalKind) : RNGkind: severe deviations from normality for Kinderman-Ramage + Marsaglia-Multicarry done successfully. Executing test function test.ls_ln ... done successfully. Executing test function test.ls_ln_svd ... done successfully. Executing test function test.lsi ... Timing stopped at: 0.002 0 0.001 Error in checkEqualsNumeric(x[1], xe[1] - 1) : Modes: logical, numeric target is logical, current is numeric done successfully. Executing test function test.lsi_ln ... Timing stopped at: 0 0.002 0.002 Error in checkEqualsNumeric(x[1], xe[1] - 1) : Modes: logical, numeric target is logical, current is numeric done successfully. Executing test function test.nlsic ... Timing stopped at: 0.002 0 0.002 Error in func() : nlsic: Unfeasible constraints at starting point (u%*%par-co>0): a >= 1 (-1) b >= 1 (-1) done successfully. RUNIT TEST PROTOCOL -- Wed Oct 23 06:21:18 2024 *********************************************** Number of test functions: 8 Number of errors: 1 Number of failures: 3 1 Test Suite : nlsic unit tests - 8 test functions, 1 error, 3 failures FAILURE in test.ldp: Error in checkEqualsNumeric(x, c(1, 0, 0)) : Modes: NULL, numeric Lengths: 0, 3 target is NULL, current is numeric FAILURE in test.lsi: Error in checkEqualsNumeric(x[1], xe[1] - 1) : Modes: logical, numeric target is logical, current is numeric FAILURE in test.lsi_ln: Error in checkEqualsNumeric(x[1], xe[1] - 1) : Modes: logical, numeric target is logical, current is numeric ERROR in test.nlsic: Error in func() : nlsic: Unfeasible constraints at starting point (u%*%par-co>0): a >= 1 (-1) b >= 1 (-1) Details *************************** Test Suite: nlsic unit tests Test function regexp: ^[Tt]est.+ Test file regexp: ^runit.+\.[rR]$ Involved directory: /home/hornik/tmp/CRAN_recheck/nlsic.Rcheck/nlsic/unitTests --------------------------- Test file: /home/hornik/tmp/CRAN_recheck/nlsic.Rcheck/nlsic/unitTests/runit.nlsic.R test.Nulla: (1 checks) ... OK (0 seconds) test.join: (1 checks) ... OK (0 seconds) test.ldp: FAILURE !! (check number 1) Error in checkEqualsNumeric(x, c(1, 0, 0)) : Modes: NULL, numeric Lengths: 0, 3 target is NULL, current is numeric test.ls_ln: (1 checks) ... OK (0 seconds) test.ls_ln_svd: (2 checks) ... OK (0 seconds) test.lsi: FAILURE !! (check number 2) Error in checkEqualsNumeric(x[1], xe[1] - 1) : Modes: logical, numeric target is logical, current is numeric test.lsi_ln: FAILURE !! (check number 2) Error in checkEqualsNumeric(x[1], xe[1] - 1) : Modes: logical, numeric target is logical, current is numeric test.nlsic: ERROR !! Error in func() : nlsic: Unfeasible constraints at starting point (u%*%par-co>0): a >= 1 (-1) b >= 1 (-1) Error: RUnit: 3 test failure(s) Execution halted Package: nmathresh Check: examples New result: ERROR Running examples in ‘nmathresh-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: nma_thresh > ### Title: Calculate thresholds and invariant intervals > ### Aliases: nma_thresh > > ### ** Examples > > # Please see the vignette "Examples" for worked examples including use of > # this function, including more information on the brief code below. > > vignette("Examples", package = "nmathresh") starting httpd help server ... done > > ### Contrast level thresholds for Thrombolytic treatments NMA > K <- 6 # Number of treatments > > # Contrast design matrix is > X <- matrix(ncol = K-1, byrow = TRUE, + c(1, 0, 0, 0, 0, + 0, 1, 0, 0, 0, + 0, 0, 1, 0, 0, + 0, 0, 0, 1, 0, + 0, -1, 1, 0, 0, + 0, -1, 0, 1, 0, + 0, -1, 0, 0, 1)) > > # Reconstruct hypothetical likelihood covariance matrix using NNLS > lik.cov <- recon_vcov(Thrombo.post.cov, prior.prec = .0001, X = X) Likelihood precisions found using NNLS. Residual Sum of Squares: 0 -------------------- RSS fixed: 0.295837 RSS fitted: 2630761 -------------------- Warning in recon_vcov(Thrombo.post.cov, prior.prec = 1e-04, X = X) : Returned some infinite variances. These will be not be included in KL calculation. Error in h(simpleError(msg, call)) : error in evaluating the argument 'a' in selecting a method for function 'solve': 'a' is 0-diml Calls: recon_vcov ... solve -> solve -> solve.default -> .handleSimpleError -> h Execution halted Package: nmathresh Check: re-building of vignette outputs New result: ERROR Error(s) in re-building vignettes: ... --- re-building ‘Examples.Rmd’ using rmarkdown ** Processing: /home/hornik/tmp/CRAN_recheck/nmathresh.Rcheck/vign_test/nmathresh/vignettes/Examples_files/figure-html/unnamed-chunk-10-1.png 3900x1650 pixels, 3x8 bits/pixel, RGB Input IDAT size = 393643 bytes Input file size = 394297 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 320111 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 320111 Output IDAT size = 320111 bytes (73532 bytes decrease) Output file size = 320189 bytes (74108 bytes = 18.79% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/nmathresh.Rcheck/vign_test/nmathresh/vignettes/Examples_files/figure-html/unnamed-chunk-11-1.png 1800x1800 pixels, 3x8 bits/pixel, RGB Input IDAT size = 134281 bytes Input file size = 134551 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 128722 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 128722 Output IDAT size = 128722 bytes (5559 bytes decrease) Output file size = 128800 bytes (5751 bytes = 4.27% decrease) Quitting from lines 179-193 [unnamed-chunk-13] (Examples.Rmd) Error: processing vignette 'Examples.Rmd' failed with diagnostics: error in evaluating the argument 'a' in selecting a method for function 'solve': 'a' is 0-diml --- failed re-building ‘Examples.Rmd’ SUMMARY: processing the following file failed: ‘Examples.Rmd’ Error: Vignette re-building failed. Execution halted Package: powdR Check: re-building of vignette outputs New result: ERROR Error(s) in re-building vignettes: ... --- re-building ‘Loading_and_manipulating.Rmd’ using rmarkdown ** Processing: /home/hornik/tmp/CRAN_recheck/powdR.Rcheck/vign_test/powdR/vignettes/Loading_and_manipulating_files/figure-html/p1-1.png 1344x1008 pixels, 3x8 bits/pixel, RGB Input IDAT size = 56385 bytes Input file size = 56535 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 52726 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 52726 Output IDAT size = 52726 bytes (3659 bytes decrease) Output file size = 52804 bytes (3731 bytes = 6.60% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/powdR.Rcheck/vign_test/powdR/vignettes/Loading_and_manipulating_files/figure-html/unnamed-chunk-10-1.png 1344x1008 pixels, 3x8 bits/pixel, RGB Input IDAT size = 109896 bytes Input file size = 110130 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 108023 zc = 9 zm = 8 zs = 1 f = 5 IDAT size = 107692 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 1 f = 5 IDAT size = 107692 Output IDAT size = 107692 bytes (2204 bytes decrease) Output file size = 107770 bytes (2360 bytes = 2.14% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/powdR.Rcheck/vign_test/powdR/vignettes/Loading_and_manipulating_files/figure-html/unnamed-chunk-11-1.png 1344x1008 pixels, 3x8 bits/pixel, RGB Input IDAT size = 105792 bytes Input file size = 106014 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 101871 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 101871 Output IDAT size = 101871 bytes (3921 bytes decrease) Output file size = 101949 bytes (4065 bytes = 3.83% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/powdR.Rcheck/vign_test/powdR/vignettes/Loading_and_manipulating_files/figure-html/unnamed-chunk-12-1.png 1344x1008 pixels, 3x8 bits/pixel, RGB Input IDAT size = 71233 bytes Input file size = 71407 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 66082 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 66082 Output IDAT size = 66082 bytes (5151 bytes decrease) Output file size = 66160 bytes (5247 bytes = 7.35% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/powdR.Rcheck/vign_test/powdR/vignettes/Loading_and_manipulating_files/figure-html/unnamed-chunk-16-1.png 1344x1008 pixels, 3x8 bits/pixel, RGB Input IDAT size = 63856 bytes Input file size = 64018 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 59761 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 59761 Output IDAT size = 59761 bytes (4095 bytes decrease) Output file size = 59839 bytes (4179 bytes = 6.53% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/powdR.Rcheck/vign_test/powdR/vignettes/Loading_and_manipulating_files/figure-html/unnamed-chunk-17-1.png 1344x1008 pixels, 3x8 bits/pixel, RGB Input IDAT size = 62411 bytes Input file size = 62573 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 58862 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 58862 Output IDAT size = 58862 bytes (3549 bytes decrease) Output file size = 58940 bytes (3633 bytes = 5.81% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/powdR.Rcheck/vign_test/powdR/vignettes/Loading_and_manipulating_files/figure-html/unnamed-chunk-18-1.png 1344x1008 pixels, 3x8 bits/pixel, RGB Input IDAT size = 81395 bytes Input file size = 81581 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 77348 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 77348 Output IDAT size = 77348 bytes (4047 bytes decrease) Output file size = 77426 bytes (4155 bytes = 5.09% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/powdR.Rcheck/vign_test/powdR/vignettes/Loading_and_manipulating_files/figure-html/unnamed-chunk-19-1.png 1344x1008 pixels, 3x8 bits/pixel, RGB Input IDAT size = 73251 bytes Input file size = 73425 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 69412 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 69412 Output IDAT size = 69412 bytes (3839 bytes decrease) Output file size = 69490 bytes (3935 bytes = 5.36% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/powdR.Rcheck/vign_test/powdR/vignettes/Loading_and_manipulating_files/figure-html/unnamed-chunk-22-1.png 1344x1008 pixels, 3x8 bits/pixel, RGB Input IDAT size = 71904 bytes Input file size = 72078 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 69107 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 69107 Output IDAT size = 69107 bytes (2797 bytes decrease) Output file size = 69185 bytes (2893 bytes = 4.01% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/powdR.Rcheck/vign_test/powdR/vignettes/Loading_and_manipulating_files/figure-html/unnamed-chunk-22-2.png 1344x1008 pixels, 3x8 bits/pixel, RGB Input IDAT size = 67860 bytes Input file size = 68034 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 65266 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 65266 Output IDAT size = 65266 bytes (2594 bytes decrease) Output file size = 65344 bytes (2690 bytes = 3.95% decrease) --- finished re-building ‘Loading_and_manipulating.Rmd’ --- re-building ‘full_pattern_summation.Rmd’ using rmarkdown ** Processing: /home/hornik/tmp/CRAN_recheck/powdR.Rcheck/vign_test/powdR/vignettes/full_pattern_summation_files/figure-html/p1-1.png 1344x1008 pixels, 3x8 bits/pixel, RGB Input IDAT size = 128711 bytes Input file size = 128969 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 IDAT size = 126874 zc = 9 zm = 8 zs = 1 f = 5 IDAT size = 126601 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 1 f = 5 IDAT size = 126601 Output IDAT size = 126601 bytes (2110 bytes decrease) Output file size = 126679 bytes (2290 bytes = 1.78% decrease) Quitting from lines 281-298 [unnamed-chunk-15] (full_pattern_summation.Rmd) Error: processing vignette 'full_pattern_summation.Rmd' failed with diagnostics: invalid 'row.names' length --- failed re-building ‘full_pattern_summation.Rmd’ SUMMARY: processing the following file failed: ‘full_pattern_summation.Rmd’ Error: Vignette re-building failed. Execution halted Package: rrcov3way Check: re-building of vignette outputs New result: ERROR Error(s) in re-building vignettes: ... --- re-building ‘rrcov3way.Rnw’ using Sweave Robust Methods for Multiway Data Analysis, Applicable also for Compositional Data (version 0.5-0) Attaching package: 'rrcov3way' The following object is masked from 'package:stats': reorder Error: processing vignette 'rrcov3way.Rnw' failed with diagnostics: chunk 41 (label = amino-allcomp) Error in cp_als(X, ncomp = ncomp, const = const, conv = conv, start = start, : Error in nonnegative LS for mode A at iter= 0 --- failed re-building 'rrcov3way.Rnw' SUMMARY: processing the following file failed: 'rrcov3way.Rnw' Error: Vignette re-building failed. Execution halted Package: rrcov3way Check: tests New result: ERROR Running ‘tparafac-err.R’ [2s/2s] Running ‘tparafac.R’ [4s/4s] Comparing ‘tparafac.Rout’ to ‘tparafac.Rout.save’ ... OK Running ‘tplots.R’ [2s/2s] Comparing ‘tplots.Rout’ to ‘tplots.Rout.save’ ... OK Running ‘ttucker3.R’ [3s/3s] Comparing ‘ttucker3.Rout’ to ‘ttucker3.Rout.save’ ... OK Running ‘tutils.R’ [2s/2s] Comparing ‘tutils.Rout’ to ‘tutils.Rout.save’ ... OK Running the tests in ‘tests/tparafac-err.R’ failed. Complete output: > ## this will render the output independent from the version of the package > suppressPackageStartupMessages(library(rrcov3way)) > > set.seed(123456) > > ## Example with the UNIDO Manufacturing value added data > data(va3way) > dim(va3way) [1] 49 5 14 > > ## Treat quickly and dirty the zeros in the data set (if any) > va3way[va3way==0] <- 0.001 > > ## IGNORE_RDIFF_BEGIN > res <- Parafac(va3way, trace=TRUE) # tracing Candecomp/Parafac function value at Start is 3.39457362294427e+24 f= 1.97957920221784e+23 after 50 iters; diff.= 8945743210706108416 f= 1.97722009973095e+23 after 100 iters; diff.= 2576101314060615680 f= 1.97634185241095e+23 after 150 iters; diff.= 1216969433998688256 f= 1.97588048976323e+23 after 200 iters; diff.= 707595978248552448 f= 1.97559562967186e+23 after 250 iters; diff.= 4.6278293851e+17 f= 1.9754019735921e+23 after 300 iters; diff.= 326500214426828800 f= 1.97526160802808e+23 after 350 iters; diff.= 242856346825785344 Candecomp/Parafac function value is 1.97517430216866e+23 after 390 iterations Fit percentage is 94.18 % > ## IGNORE_RDIFF_END > > ## Using robustness with clr transformation > try(res <- Parafac(va3way, robust=TRUE, coda.transform="clr")) Error in Parafac(va3way, robust = TRUE, coda.transform = "clr") : The robust option is not possible with 'clr' transform compositional data. Please use 'ilr'. > > ## Rejected values of parameter 'crit' > try(res <- Parafac(va3way, crit=c(1:10))) # length different than 1 Error in Parafac(va3way, crit = c(1:10)) : 'crit' has to be a single positive number less than 1! > try(res <- Parafac(va3way, crit=-1)) # crit non-positive Error in Parafac(va3way, crit = -1) : 'crit' has to be a single positive number less than 1! > try(res <- Parafac(va3way, crit=2)) # crit >= 1 Error in Parafac(va3way, crit = 2) : 'crit' has to be a single positive number less than 1! > > res <- Parafac(va3way, crit=0.2) # crit < 0.5 --> crit=1-crit > > ## Test cp_als(): the input array > try(rrcov3way:::cp_als(va3way)) # missing ncomp Error in rrcov3way:::cp_als(va3way) : Number of factors to extract 'ncomp' must be provided! > > set.seed(98765) > rrcov3way:::cp_als(va3way, ncomp=2) # OK, 3-way array $fit [1] 1.975173e+23 $fp [1] 94.18138 $ss [1] 3.394574e+24 $A [,1] [,2] [1,] 75325306 184384923 [2,] -8222132158 -706325609 [3,] -10028635776 -2304869333 [4,] -9235645113 49236012457 [5,] 144204886 1162123010 [6,] -9209273813 22182444692 [7,] -15970577022 -5563332563 [8,] 2433687877 9337493282 [9,] 438478268 1340749311 [10,] 184203532 536581878 [11,] -5397073344 -910008700 [12,] -6232934360 -2616449170 [13,] 1270743122 3238798585 [14,] 113709848 611006478 [15,] -3816120588 930010937 [16,] -39994050458 -8031850169 [17,] 84247398 219875097 [18,] 175740842 415243568 [19,] -164239813087 -118774189733 [20,] -4584857904 -2257019456 [21,] -8658993135 13953903478 [22,] 1274473021 17017890520 [23,] -5952142672 1026172289 [24,] -2129113144 589425432 [25,] -31133743039 7226820838 [26,] 206665027 1079920182 [27,] -58368100072 -24155348523 [28,] 215145457 668876766 [29,] 200411814 877350610 [30,] 300673966 653811419 [31,] -181139313 853856931 [32,] -11024715690 -1554598944 [33,] -2531525584 1306423795 [34,] 2774399686 7518193077 [35,] -3475833077 7297305407 [36,] 410954020 4829122549 [37,] -1295493028 207181313 [38,] -290912976 2503807639 [39,] 6477968044 43767955751 [40,] 50996412 193932515 [41,] -10497983292 -9500681476 [42,] -1077176286 316975234 [43,] -1416666704 -465133849 [44,] -11782349711 11394183501 [45,] -12425813012 -5924237992 [46,] -20709472397 -14016083131 [47,] -599892851 11440591554 [48,] -35925845820 -6985682064 [49,] 543484639 1141458655 $B [,1] [,2] [1,] -2.0128950 1.5744456 [2,] -0.5515332 0.2866199 [3,] -2.5352626 1.7014215 [4,] -3.2963694 1.2415543 [5,] -0.9844209 0.4270625 $C [,1] [,2] [1,] 0.4513023 0.4748265 [2,] 0.4354471 0.4486442 [3,] 0.4495636 0.4582773 [4,] 0.5377859 0.5428363 [5,] 0.6248667 0.6467386 [6,] 0.6700282 0.7527217 [7,] 0.7423040 0.8659029 [8,] 0.8542403 1.0232329 [9,] 0.8970301 1.1423872 [10,] 0.7238015 0.9159853 [11,] 0.8763976 1.1605787 [12,] 0.9842029 1.3208483 [13,] 0.9215009 1.2585477 [14,] 0.9485225 1.2769873 $iter [1] 391 $tripcos Minimal triple cosine -0.7333024 $mintripcos [1] -0.7330044 $ftiter [,1] [,2] [1,] 2.044477e+23 -0.02491081 [2,] 1.987935e+23 -0.15798293 [3,] 1.983906e+23 -0.25618180 [4,] 1.981542e+23 -0.32907730 [5,] 1.980056e+23 -0.38454241 [6,] 1.979078e+23 -0.42773241 [7,] 1.978404e+23 -0.46214450 [8,] 1.977914e+23 -0.49019938 [9,] 1.977540e+23 -0.51358224 [10,] 1.977244e+23 -0.53347032 [11,] 1.977002e+23 -0.55069138 [12,] 1.976800e+23 -0.56583357 [13,] 1.976627e+23 -0.57932069 [14,] 1.976478e+23 -0.59146337 [15,] 1.976348e+23 -0.60249357 [16,] 1.976233e+23 -0.61258794 [17,] 1.976132e+23 -0.62188363 [18,] 1.976040e+23 -0.63048922 [19,] 1.975958e+23 -0.63849211 [20,] 1.975884e+23 -0.64596385 [21,] 1.975816e+23 -0.65296382 [22,] 1.975755e+23 -0.65954195 [23,] 1.975698e+23 -0.66574067 [24,] 1.975646e+23 -0.67159639 [25,] 1.975598e+23 -0.67714061 [26,] 1.975553e+23 -0.68240080 [27,] 1.975512e+23 -0.68740104 [28,] 1.975473e+23 -0.69216260 [29,] 1.975437e+23 -0.69670431 [30,] 1.975404e+23 -0.70104296 [31,] 1.975372e+23 -0.70519358 [32,] 1.975342e+23 -0.70916965 [33,] 1.975314e+23 -0.71298331 [34,] 1.975288e+23 -0.71664555 [35,] 1.975263e+23 -0.72016633 [36,] 1.975239e+23 -0.72355471 [37,] 1.975217e+23 -0.72681892 [38,] 1.975195e+23 -0.72996653 [39,] 1.975175e+23 -0.73300444 $const [1] "none" "none" "none" > rrcov3way:::cp_als(unfold(va3way), ncomp=2, + n=49, m=5, p=14) # OK, unfolded 3-way array $fit [1] 1.975174e+23 $fp [1] 94.18138 $ss [1] 3.394574e+24 $A [,1] [,2] [1,] -156564243 -11456778 [2,] 599513414 1250657041 [3,] 1956821842 1525434201 [4,] -41807974113 1405061113 [5,] -986787462 -21929308 [6,] -18836037766 1400918173 [7,] 4723534010 2429245748 [8,] -7928658980 -370141270 [9,] -1138455151 -66690074 [10,] -455621198 -28016430 [11,] 772551768 820939162 [12,] 2221514693 948073091 [13,] -2750117993 -193276005 [14,] -518819361 -17293346 [15,] -789811887 580471006 [16,] 6818854768 6083415859 [17,] -186699695 -12813739 [18,] -352589852 -26729780 [19,] 100849540296 24981781676 [20,] 1916361413 697387429 [21,] -11848915345 1317177994 [22,] -14450331668 -193776767 [23,] -871533105 905379297 [24,] -500558962 323860508 [25,] -6137440276 4735757215 [26,] -916984791 -31430449 [27,] 20509285255 8878204475 [28,] -567955637 -32722343 [29,] -744977018 -30480210 [30,] -555160662 -45732074 [31,] -725038606 27557124 [32,] 1319722255 1676951229 [33,] -1109394850 385074466 [34,] -6383828493 -421975245 [35,] -6196452463 528740681 [36,] -4100531837 -62486577 [37,] -175959890 197057446 [38,] -2126061422 44262650 [39,] -37164427796 -985148404 [40,] -164672091 -7756087 [41,] 8066991941 1596793500 [42,] -269184257 163849842 [43,] 394915428 215485519 [44,] -9675485438 1792255555 [45,] 5030059762 1890049308 [46,] 11900839685 3150031372 [47,] -9714550026 91303871 [48,] 5930656686 5464611411 [49,] -969228878 -82663471 $B [,1] [,2] [1,] -1.2824706 1.9007237 [2,] -0.2334633 0.5208042 [3,] -1.3858919 2.3939934 [4,] -1.0112777 3.1127308 [5,] -0.3478557 0.9295767 $C [,1] [,2] [1,] 0.6864742 3.141965 [2,] 0.6486208 3.031583 [3,] 0.6625473 3.129863 [4,] 0.7847967 3.744067 [5,] 0.9350131 4.350321 [6,] 1.0882414 4.664728 [7,] 1.2518745 5.167906 [8,] 1.4793353 5.947201 [9,] 1.6516066 6.245093 [10,] 1.3242857 5.039082 [11,] 1.6779094 6.101444 [12,] 1.9096206 6.851978 [13,] 1.8195509 6.415446 [14,] 1.8462089 6.603572 $iter [1] 373 $tripcos Minimal triple cosine -0.73327 $mintripcos [1] -0.7323726 $ftiter [,1] [,2] [1,] 2.003601e+23 -0.2336666 [2,] 1.982150e+23 -0.3105052 [3,] 1.980420e+23 -0.3706370 [4,] 1.979306e+23 -0.4172073 [5,] 1.978553e+23 -0.4540189 [6,] 1.978017e+23 -0.4837758 [7,] 1.977617e+23 -0.5083737 [8,] 1.977304e+23 -0.5291408 [9,] 1.977051e+23 -0.5470095 [10,] 1.976840e+23 -0.5626396 [11,] 1.976662e+23 -0.5765030 [12,] 1.976508e+23 -0.5889431 [13,] 1.976374e+23 -0.6002138 [14,] 1.976257e+23 -0.6105068 [15,] 1.976152e+23 -0.6199697 [16,] 1.976059e+23 -0.6287183 [17,] 1.975975e+23 -0.6368453 [18,] 1.975899e+23 -0.6444258 [19,] 1.975830e+23 -0.6515221 [20,] 1.975767e+23 -0.6581863 [21,] 1.975710e+23 -0.6644623 [22,] 1.975657e+23 -0.6703879 [23,] 1.975608e+23 -0.6759956 [24,] 1.975562e+23 -0.6813137 [25,] 1.975520e+23 -0.6863670 [26,] 1.975481e+23 -0.6911772 [27,] 1.975445e+23 -0.6957639 [28,] 1.975411e+23 -0.7001441 [29,] 1.975378e+23 -0.7043332 [30,] 1.975348e+23 -0.7083450 [31,] 1.975320e+23 -0.7121920 [32,] 1.975293e+23 -0.7158853 [33,] 1.975268e+23 -0.7194351 [34,] 1.975244e+23 -0.7228507 [35,] 1.975221e+23 -0.7261405 [36,] 1.975200e+23 -0.7293121 [37,] 1.975179e+23 -0.7323726 $const [1] "none" "none" "none" > > try(rrcov3way:::cp_als("abc", ncomp=2)) # error, not an array or matrix Error in rrcov3way:::cp_als("abc", ncomp = 2) : 'X' must be three dimensional array or a matrix! > > try(rrcov3way:::cp_als(unfold(va3way), ncomp=2))# missing dimensions Error in rrcov3way:::cp_als(unfold(va3way), ncomp = 2) : The three dimensions of the matricisized array must be provided! > try(rrcov3way:::cp_als(unfold(va3way), ncomp=2, + n=50, m=5, p=14)) # n != dim(Xa)[1] Error in rrcov3way:::cp_als(unfold(va3way), ncomp = 2, n = 50, m = 5, : 'n' must be equal to the first dimension of the matrix 'X'! > try(rrcov3way:::cp_als(unfold(va3way), ncomp=2, + n=49, m=1, p=14)) # m*p != dim(Xa)[2] Error in rrcov3way:::cp_als(unfold(va3way), ncomp = 2, n = 49, m = 1, : 'm*p' must be equal to the second dimension of the matrix 'X'! > > ## Test cp_als(): the constraints > try(Parafac(va3way, const="abc")) # wrong constraint Error in cp_als(X, ncomp = ncomp, const = const, conv = conv, start = start, : All elements of 'const' must be one of 'none', 'orth', 'nonneg' or 'zerocor' > res <- Parafac(va3way, const=c("none", "none")) # length of const < 3 > res$const [1] "none" "none" "none" > > ## Test cp_als(): the initial values > try(Parafac(va3way, start=c(1:2))) # wrong start Error in cp_als(X, ncomp = ncomp, const = const, conv = conv, start = start, : 'start' must be either a list with elements A, B and C or a single character - one of 'random' or 'svd'! > try(Parafac(va3way, start="abc")) # wrong start Error in cp_als(X, ncomp = ncomp, const = const, conv = conv, start = start, : 'start' must be either a list with elements A, B and C or one of 'random' or 'svd'! > > Parafac(va3way, start="svd") Call: Parafac(X = va3way, start = "svd") PARAFAC analysis with 2 components. Fit value: 1.975174e+23 Fit percentage: 94.18 % > Parafac(va3way, const="nonneg", start="svd") Error in cp_als(X, ncomp = ncomp, const = const, conv = conv, start = start, : Error in nonnegative LS for mode A at iter= 0 Calls: Parafac -> .Parafac -> cp_als Execution halted Package: smacof Check: examples New result: ERROR Running examples in ‘smacof-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: smacofSym > ### Title: Symmetric smacof > ### Aliases: smacofSym mds > ### Keywords: multivariate > > ### ** Examples > > > ## simple SMACOF solution (interval MDS) for kinship data > res <- mds(kinshipdelta, type = "interval") > res Call: mds(delta = kinshipdelta, type = "interval") Model: Symmetric SMACOF Number of objects: 15 Stress-1 value: 0.264 Number of iterations: 62 > summary(res) Configurations: D1 D2 Aunt -0.2396 0.6564 Brother 0.4155 -0.5273 Cousin 0.2229 0.8487 Daughter -0.3984 -0.3781 Father 0.1659 -0.6753 Granddaughter -0.5294 0.1352 Grandfather 0.7014 -0.1224 Grandmother -0.6953 0.1544 Grandson 0.5288 -0.0998 Mother -0.4395 -0.5605 Nephew 0.3974 0.3915 Niece -0.2684 0.5293 Sister -0.5923 -0.3151 Son 0.2058 -0.5073 Uncle 0.5251 0.4701 Stress per point (in %): Aunt Brother Cousin Daughter Father 6.01 7.46 5.82 3.85 4.76 Granddaughter Grandfather Grandmother Grandson Mother 8.81 11.55 11.76 8.81 4.86 Nephew Niece Sister Son Uncle 4.74 4.22 7.42 4.06 5.88 > plot(res) > plot(res, type = "p", label.conf = list(label = TRUE, col = "darkgray"), pch = 25, col = "red") > > ## ratio MDS, random starts > set.seed(123) > res <- mds(kinshipdelta, init = "random") > res Call: mds(delta = kinshipdelta, init = "random") Model: Symmetric SMACOF Number of objects: 15 Stress-1 value: 0.284 Number of iterations: 198 > > ## 3D ordinal SMACOF solution for trading data (secondary approach to ties) > data(trading) > res <- mds(trading, ndim = 3, type = "ordinal", ties = "secondary") > res Call: mds(delta = trading, ndim = 3, type = "ordinal", ties = "secondary") Model: Symmetric SMACOF Number of objects: 20 Stress-1 value: 0.106 Number of iterations: 34 > > ## spline MDS > delta <- sim2diss(cor(PVQ40agg)) > res <- mds(delta, type = "mspline", spline.degree = 3, spline.intKnots = 4) Error in if (((sold - snon) < eps) || (itel == itmax)) (break)() : missing value where TRUE/FALSE needed Calls: mds Execution halted Package: smacof Check: re-building of vignette outputs New result: ERROR Error(s) in re-building vignettes: ... --- re-building ‘mdsnutshell.Rmd’ using rmarkdown ** Processing: /home/hornik/tmp/CRAN_recheck/smacof.Rcheck/vign_test/smacof/vignettes/mdsnutshell_files/figure-html/wenmds2-1.png 480x480 pixels, 8 bits/pixel, 256 colors in palette Reducing image to 8 bits/pixel, grayscale Input IDAT size = 11462 bytes Input file size = 12332 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 10443 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 10443 Output IDAT size = 10443 bytes (1019 bytes decrease) Output file size = 10521 bytes (1811 bytes = 14.69% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/smacof.Rcheck/vign_test/smacof/vignettes/mdsnutshell_files/figure-html/wenmds2-2.png 480x480 pixels, 8 bits/pixel, 256 colors in palette Reducing image to 8 bits/pixel, grayscale Input IDAT size = 11619 bytes Input file size = 12489 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 10591 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 10591 Output IDAT size = 10591 bytes (1028 bytes decrease) Output file size = 10669 bytes (1820 bytes = 14.57% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/smacof.Rcheck/vign_test/smacof/vignettes/mdsnutshell_files/figure-html/confplot-1.png 576x576 pixels, 8 bits/pixel, 256 colors in palette Reducing image to 8 bits/pixel, grayscale Input IDAT size = 11727 bytes Input file size = 12597 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 10574 zc = 9 zm = 8 zs = 1 f = 0 IDAT size = 10543 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 1 f = 0 IDAT size = 10543 Output IDAT size = 10543 bytes (1184 bytes decrease) Output file size = 10621 bytes (1976 bytes = 15.69% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/smacof.Rcheck/vign_test/smacof/vignettes/mdsnutshell_files/figure-html/ggconf-1.png 576x576 pixels, 8 bits/pixel, 256 colors in palette Reducing image to 8 bits/pixel, grayscale Input IDAT size = 10939 bytes Input file size = 11809 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 9721 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 9721 Output IDAT size = 9721 bytes (1218 bytes decrease) Output file size = 9799 bytes (2010 bytes = 17.02% decrease) --- finished re-building ‘mdsnutshell.Rmd’ --- re-building ‘unfoldingnutshell.Rmd’ using rmarkdown ** Processing: /home/hornik/tmp/CRAN_recheck/smacof.Rcheck/vign_test/smacof/vignettes/unfoldingnutshell_files/figure-html/breakconf-1.png 576x576 pixels, 3x8 bits/pixel, RGB Input IDAT size = 40457 bytes Input file size = 40583 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 31644 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 31644 Output IDAT size = 31644 bytes (8813 bytes decrease) Output file size = 31722 bytes (8861 bytes = 21.83% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/smacof.Rcheck/vign_test/smacof/vignettes/unfoldingnutshell_files/figure-html/privconf-1.png 576x576 pixels, 3x8 bits/pixel, RGB Input IDAT size = 38649 bytes Input file size = 38775 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 28662 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 28662 Output IDAT size = 28662 bytes (9987 bytes decrease) Output file size = 28740 bytes (10035 bytes = 25.88% decrease) ** Processing: /home/hornik/tmp/CRAN_recheck/smacof.Rcheck/vign_test/smacof/vignettes/unfoldingnutshell_files/figure-html/ggconfu-1.png 576x576 pixels, 3x8 bits/pixel, RGB Input IDAT size = 36520 bytes Input file size = 36646 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 28927 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 28927 Output IDAT size = 28927 bytes (7593 bytes decrease) Output file size = 29005 bytes (7641 bytes = 20.85% decrease) --- finished re-building ‘unfoldingnutshell.Rmd’ --- re-building ‘smacof.Rnw’ using knitr Quitting from lines 188-195 [intelligence] (smacof.Rnw) Error: processing vignette 'smacof.Rnw' failed with diagnostics: missing value where TRUE/FALSE needed --- failed re-building ‘smacof.Rnw’ SUMMARY: processing the following file failed: ‘smacof.Rnw’ Error: Vignette re-building failed. Execution halted Package: SuperLearner Check: re-building of vignette outputs New result: ERROR Error(s) in re-building vignettes: ... --- re-building ‘Guide-to-SuperLearner.Rmd’ using rmarkdown Boston package:MASS R Documentation _H_o_u_s_i_n_g _V_a_l_u_e_s _i_n _S_u_b_u_r_b_s _o_f _B_o_s_t_o_n _D_e_s_c_r_i_p_t_i_o_n: The 'Boston' data frame has 506 rows and 14 columns. _U_s_a_g_e: Boston _F_o_r_m_a_t: This data frame contains the following columns: 'crim' per capita crime rate by town. 'zn' proportion of residential land zoned for lots over 25,000 sq.ft. 'indus' proportion of non-retail business acres per town. 'chas' Charles River dummy variable (= 1 if tract bounds river; 0 otherwise). 'nox' nitrogen oxides concentration (parts per 10 million). 'rm' average number of rooms per dwelling. 'age' proportion of owner-occupied units built prior to 1940. 'dis' weighted mean of distances to five Boston employment centres. 'rad' index of accessibility to radial highways. 'tax' full-value property-tax rate per $10,000. 'ptratio' pupil-teacher ratio by town. 'black' 1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town. 'lstat' lower status of the population (percent). 'medv' median value of owner-occupied homes in $1000s. _S_o_u_r_c_e: Harrison, D. and Rubinfeld, D.L. (1978) Hedonic prices and the demand for clean air. _J. Environ. Economics and Management_ *5*, 81-102. Belsley D.A., Kuh, E. and Welsch, R.E. (1980) _Regression Diagnostics. Identifying Influential Data and Sources of Collinearity._ New York: Wiley. Quitting from lines 191-213 [predict] (Guide-to-SuperLearner.Rmd) Error: processing vignette 'Guide-to-SuperLearner.Rmd' failed with diagnostics: incorrect number of dimensions --- failed re-building ‘Guide-to-SuperLearner.Rmd’ SUMMARY: processing the following file failed: ‘Guide-to-SuperLearner.Rmd’ Error: Vignette re-building failed. Execution halted Package: TIMP Check: examples New result: ERROR Running examples in ‘TIMP-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: kin-class > ### Title: Class "kin" for kinetic model storage. > ### Aliases: kin-class kin > ### Keywords: classes > > ### ** Examples > > ## Example in modeling second order kinetics, by > ## David Nicolaides. > > ## On simulated data. > > ############################## > ## load TIMP > ############################## > > library("TIMP") > > ############################## > ## SIMULATE DATA > ############################## > > ## set up the Example problem, a la in-situ UV-Vis spectroscopy of a simple > ## reaction. > ## A + 2B -> C + D, 2C -> E > > cstart <- c(A = 1.0, B = 0.8, C = 0.0, D = 0.0, E = 0.0) > times <- c(seq(0,2, length=21), seq(3,10, length=8)) > k <- c(kA = 0.5, k2C = 1) > > ## stoichiometry matrices > > rsmatrix <- c(1,2,0,0,0,0,0,2,0,0) > smatrix <- c(-1,-2,1,1,0,0,0,-2,0,1) > concentrations <- calcD(k, times, cstart, rsmatrix, smatrix) > > wavelengths <- seq(500, 700, by=2) > spectra <- matrix(nrow = length(wavelengths), ncol = length(cstart)) > location <- c(550, 575, 625, 650, 675) > delta <- c(10, 10, 10, 10, 10) > spectra[, 1] <- exp( - log(2) * + (2 * (wavelengths - location[1])/delta[1])^2) > spectra[, 2] <- exp( - log(2) * + (2 * (wavelengths - location[2])/delta[2])^2) > spectra[, 3] <- exp( - log(2) * + (2 * (wavelengths - location[3])/delta[3])^2) > spectra[, 4] <- exp( - log(2) * + (2 * (wavelengths - location[4])/delta[4])^2) > spectra[, 5] <- exp( - log(2) * + (2 * (wavelengths - location[5])/delta[5])^2) > > sigma <- .001 > Psi_q <- concentrations %*% t(spectra) + sigma * + rnorm(dim(concentrations)[1] * dim(spectra)[1]) > > ## store the simulated data in an object of class "dat" > kinetic_data <- dat(psi.df=Psi_q , x = times, nt = length(times), + x2 = wavelengths, nl = length(wavelengths)) > > ############################## > ## DEFINE MODEL > ############################## > > ## starting values > kstart <- c(kA = 1, k2C = 0.5) > > ## model definition for 2nd order kinetics > kinetic_model <- initModel(mod_type = "kin", seqmod = FALSE, + kinpar = kstart, + numericalintegration = TRUE, + initialvals = cstart, + reactantstoichiometrymatrix = rsmatrix, + stoichiometrymatrix = smatrix ) > > ############################## > ## FIT INITIAL MODEL > ## adding constraints to non-negativity of the > ## spectra via the opt option nnls=TRUE > ############################## > > kinetic_fit <- fitModel(data=list(kinetic_data), + modspec = list(kinetic_model), + opt = kinopt(nnls = TRUE, iter=80, + selectedtraces = seq(1,kinetic_data@nl,by=2))) Error in nlsModel(formula, mf, start, wts, scaleOffset = scOff, nDcentral = nDcntr) : singular gradient matrix at initial parameter estimates Calls: fitModel -> nls -> nlsModel Execution halted Package: TIMP Check: tests New result: ERROR Running ‘example2nd.R’ [1s/1s] Running ‘kin_sim_large_script.R’ [3s/3s] Running ‘kin_simple_ir_script.R’ [1s/1s] Running ‘kin_simple_visible_script.R’ [5s/5s] Running ‘kin_target_script.R’ [2s/2s] Running ‘spectral_script.R’ [3s/4s] Running the tests in ‘tests/example2nd.R’ failed. Complete output: > ## Example in modeling second order kinetics, by > ## David Nicolaides. > > ## On simulated data. > > ############################## > ## load TIMP > ############################## > > library("TIMP") Loading required package: fields Loading required package: spam Spam version 2.11-0 (2024-10-03) is loaded. Type 'help( Spam)' or 'demo( spam)' for a short introduction and overview of this package. Help for individual functions is also obtained by adding the suffix '.spam' to the function name, e.g. 'help( chol.spam)'. Attaching package: 'spam' The following objects are masked from 'package:base': backsolve, forwardsolve Loading required package: viridisLite Try help(fields) to get started. > > ############################## > ## SIMULATE DATA > ############################## > > ## set up the Example problem, a la in-situ UV-Vis spectroscopy of a simple > ## reaction. > ## A + 2B -> C + D, 2C -> E > > cstart <- c(A = 1.0, B = 0.8, C = 0.0, D = 0.0, E = 0.0) > times <- c(seq(0, 2, length = 21), seq(3, 10, length = 8)) > k <- c(kA = 0.5, k2C = 1) > > ## stoichiometry matrices as per > ## Puxty, G., Maeder, M., and Hungerbuhler, K. (2006) Tutorial on the fitting > ## of kinetics models to multivariate spectroscopic measurements with > ## non-linear least-squares regression, Chemometrics and Intelligent > ## Laboratory Systems 81, 149-164. > > rsmatrix <- c(1, 2, 0, 0, 0, 0, 0, 2, 0, 0) > smatrix <- c(-1, -2, 1, 1, 0, 0, 0, -2, 0, 1) > concentrations <- calcD(k, times, cstart, rsmatrix, smatrix) > > wavelengths <- seq(500, 700, by = 2) > spectra <- matrix(nrow = length(wavelengths), ncol = length(cstart)) > location <- c(550, 575, 625, 650, 675) > delta <- c(10, 10, 10, 10, 10) > spectra[, 1] <- exp(-log(2) * (2 * (wavelengths - location[1]) / delta[1])^2) > spectra[, 2] <- exp(-log(2) * (2 * (wavelengths - location[2]) / delta[2])^2) > spectra[, 3] <- exp(-log(2) * (2 * (wavelengths - location[3]) / delta[3])^2) > spectra[, 4] <- exp(-log(2) * (2 * (wavelengths - location[4]) / delta[4])^2) > spectra[, 5] <- exp(-log(2) * (2 * (wavelengths - location[5]) / delta[5])^2) > > sigma <- .001 > Psi_q <- concentrations %*% t(spectra) + sigma * + rnorm(dim(concentrations)[1] * dim(spectra)[1]) > > ## store the simulated data in an object of class "dat" > kinetic_data <- dat( + psi.df = Psi_q, x = times, nt = length(times), + x2 = wavelengths, nl = length(wavelengths) + ) > > ############################## > ## DEFINE MODEL > ############################## > > ## starting values > kstart <- c(kA = 1, k2C = 0.5) > > ## model definition for 2nd order kinetics > kinetic_model <- initModel( + mod_type = "kin", seqmod = FALSE, kinpar = kstart, + numericalintegration = TRUE, + initialvals = cstart, + reactantstoichiometrymatrix = rsmatrix, + stoichiometrymatrix = smatrix + ) > > ############################## > ## FIT INITIAL MODEL > ## adding constraints to non-negativity of the > ## spectra via the opt option nnls=TRUE > ############################## > > kinetic_fit <- fitModel( + data = list(kinetic_data), modspec = list(kinetic_model), + opt = kinopt( + nnls = TRUE, iter = 80, + selectedtraces = seq(1, kinetic_data@nl, by = 2) + ) + ) Error in nlsModel(formula, mf, start, wts, scaleOffset = scOff, nDcentral = nDcntr) : singular gradient matrix at initial parameter estimates Calls: fitModel -> nls -> nlsModel Execution halted