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Type 'q()' to quit R. > # Run all unit tests, i.e. all checks of all test-functions > # > # Author: Andre Schuetzenmeister > ############################################################################### > > library(VCA) > library(RUnit) > > # enable/disable time-consuming model 1 and model 2 testcases with real-world data > # see file "runit.VCAinference.R" > > realWorldModel2 <- FALSE > realWorldModel1 <- FALSE > # large dataset leads to out of memory errors in many testing-environments > runTF033.runit.anovaVCA.r <- FALSE > > options(warn=1) > > # current working directory > wd <- getwd() > > # set path from wd, where RunAllTests.R resided to RUnit test-scripts (scripts directory) > sd <- "./runit/UnitTests" > tc.path <- sub("\\./", "/", paste0(wd, sd)) > > # test function regexpr fits to string "TFxyz" which are used as identifiers for easier referencing > > testSuite <- defineTestSuite(name="VCA", dirs=tc.path, + testFileRegexp="runit.*\\.R$", + testFuncRegexp = "^TF[[:digit:]]{3}.+", # use custom regexpr for test functions + rngKind="default", + rngNormalKind="default") > > > testData <- runTestSuite(testSuite, verbose=0L) *************************************************************************** Variance Component Analysis (VCA) - test cases for function 'VCAinference'. *************************************************************************** Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! SAS PROC MIXED uses the inverse of the Fisher-Information Matrix as approximation of Covariance-Matrix of Variance Components. This is equal to the one obtained via ANOVA-approach stated in "Variance Components" (Searle et al. 1991) in case of balanced designs, otherwise Var(VC) of both results may differ: SAS_Est R_Est SAS_LCL R_LCL SAS_UCL R_UCL lot 0.01377 0.01377 -0.013750 -0.016870 0.041280 0.044400 device 0.06190 0.06190 -0.062340 -0.063040 0.186100 0.186800 lot:device:day 0.01235 0.01235 -0.004180 -0.004480 0.028870 0.029180 lot:device:day:run 0.05125 0.05125 0.033110 0.032950 0.069400 0.069560 error 0.00118 0.00118 0.000932 0.000932 0.001543 0.001543 Est_Diff LCL_Diff UCL_Diff lot 0 0.00312 -0.00312 device 0 0.00070 -0.00070 lot:device:day 0 0.00030 -0.00031 lot:device:day:run 0 0.00016 -0.00016 error 0 0.00000 0.00000 Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! SAS PROC MIXED uses the inverse of the Fisher-Information Matrix as approximation of Covariance-Matrix of Variance Components. This is equal to the one obtained via ANOVA-approach stated in "Variance Components" (Searle et al. 1991) in case of balanced designs, otherwise Var(VC) of both results may differ: SAS_Est R_Est SAS_LCL R_LCL SAS_UCL R_UCL Est_Diff lot 0.18920 0.18920 -0.19090 -0.21540 0.56920 0.59380 0 device 0.43590 0.43590 -0.46080 -0.45200 1.33260 1.32380 0 lot:device:day 0.31780 0.31780 0.18600 0.18680 0.44960 0.44870 0 lot:device:day:run 0.05724 0.05724 0.02931 0.02931 0.08517 0.08517 0 error 0.04108 0.04108 0.03241 0.03241 0.05376 0.05376 0 LCL_Diff UCL_Diff lot 0.0245 -0.0246 device -0.0088 0.0088 lot:device:day -0.0008 0.0009 lot:device:day:run 0.0000 0.0000 error 0.0000 0.0000 Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! SAS PROC MIXED uses the inverse of the Fisher-Information Matrix as approximation of Covariance-Matrix of Variance Components. This is equal to the one obtained via ANOVA-approach stated in "Variance Components" (Searle et al. 1991) in case of balanced designs, otherwise Var(VC) of both results may differ: SAS_Est R_Est SAS_LCL R_LCL SAS_UCL lot -0.000850 -0.000850 -0.001540 -0.001690 -1.700e-04 device 0.058040 0.058040 -0.057620 -0.058080 1.737e-01 lot:device:day -0.017410 -0.017410 -0.034820 -0.035110 -3.250e-06 lot:device:day:run 0.084000 0.084000 0.053940 0.054130 1.141e-01 error 0.000337 0.000337 0.000266 0.000266 4.400e-04 R_UCL Est_Diff LCL_Diff UCL_Diff lot -0.00002000 0 0.00015 -0.00015000 device 0.17420000 0 0.00046 -0.00050000 lot:device:day 0.00028594 0 0.00029 -0.00028919 lot:device:day:run 0.11390000 0 -0.00019 0.00020000 error 0.00044000 0 0.00000 0.00000000 Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! Warning in VCAinference(fit, ci.method = "satterthwaite") : Point estimate(s) of VC(s) 'Site:Day:Run' found outside of confidence interval, CI was set to 'NA'! Inference from (V)ariance (C)omponent (A)nalysis ------------------------------------------------ > VC: ----- Estimate DF CI LCL CI UCL One-Sided LCL One-Sided UCL total 0.3405 15.5385 0.1875 0.8005 0.2059 0.6927 Site 0.1381 2.6726 0.0423 2.4767 0.0510 1.4414 Site:Day 0.0084 0.4506 0.0012 36811.9725 0.0017 1697.8716 Site:Day:Run 0.0004 0.0005 Inf error 0.1936 80.0000 0.1452 0.2710 0.1520 0.2564 95% Confidence Level Satterthwaite methodology used for computing CIs boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') ************************************************************************** Variance Component Analysis (VCA) - test cases defined in runit.anovaMM.R. ************************************************************************** Error in anovaMM() : argument "form" is missing, with no default Error in anovaMM(Data = 1) : argument "form" is missing, with no default Error in anovaMM(Data = data.frame()) : argument "form" is missing, with no default Error in anovaMM(Data = data.frame(y = 1:10)) : argument "form" is missing, with no default Error in orderData(Data, tobj, quiet = quiet, order.data = order.data) : all(vars %in% colnames(Data)) is not TRUE Error in orderData(Data, tobj, quiet = quiet, order.data = order.data) : all(vars %in% colnames(Data)) is not TRUE There are 3 missing values for the response variable (obs: 43, 57, 66)! Variable 'run' has 3 missing values (obs: 19, 38, 50)! Variable 'day' has 3 missing values (obs: 78, 79, 80)! Convert variable Site from "character" to "factor"! Convert variable ID from "character" to "factor"! Warning in anovaMM(y ~ day + cov + day:(run), dat1) : All values of response variable 'y' are equal! Warning in anovaMM(y ~ day/(run), dat1) : All values of response variable 'y' are equal! Warning in anovaMM(y ~ (day)/(run), dat1) : All values of response variable 'y' are equal! *********************************************************************** Variance Component Analysis (VCA) - test cases for function 'anovaVCA'. *********************************************************************** Error in anovaVCA() : argument "form" is missing, with no default Error in anovaVCA(Data = 1) : argument "form" is missing, with no default Error in anovaVCA(Data = data.frame()) : argument "form" is missing, with no default Error in anovaVCA(Data = data.frame(y = 1:10)) : argument "form" is missing, with no default Error in orderData(Data, tobj, quiet = quiet, exclude.numeric = FALSE, : all(vars %in% colnames(Data)) is not TRUE Error in orderData(Data, tobj, quiet = quiet, exclude.numeric = FALSE, : all(vars %in% colnames(Data)) is not TRUE There are 3 missing values for the response variable (obs: 43, 57, 66)! Variable 'day' has 3 missing values (obs: 78, 79, 80)! Variable 'run' has 3 missing values (obs: 19, 38, 50)! Warning in anovaVCA(y ~ day, dat1) : All values of response variable 'y' are equal! Warning in anovaVCA(y ~ day/run, dat1) : All values of response variable 'y' are equal! Error in anovaVCA(y ~ day, dataEP05A2_3[seq(1, 77, 4), ]) : Variable 'day': number of levels of each grouping factor must be < number of observations! *********************************************************************** Variance Component Analysis (VCA) - test cases defined in runit.misc.R. *********************************************************************** boundary (singular) fit: see help('isSingular') Mixed model equations solved locally. Results could not be assigned to object! Warning in lsmMat(obj, NULL, quiet = quiet) : 'Sex:age2' is "numeric", LS Means cannot be estimated,'Sex:age2' will be skipped! Warning in lsmMat(obj, NULL, quiet = quiet) : 'Sex:age2' is "numeric", LS Means cannot be estimated,'Sex:age2' will be skipped! Warning in lsmMat(obj, NULL, quiet = quiet) : 'Sex:age2' is "numeric", LS Means cannot be estimated,'Sex:age2' will be skipped! [1] TRUE [1] TRUE [1] TRUE [1] TRUE [1] TRUE [1] TRUE Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Mixed model equations were solved but results could not be assigned to 'VCA' object! Mixed model equations were solved but results could not be assigned to 'VCA' object! Mixed model equations were solved but results could not be assigned to 'VCA' object! Mixed model equations were solved but results could not be assigned to 'VCA' object! Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object! Mixed model equations were solved but results could not be assigned to 'VCA' object! Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object! Mixed model equations were solved but results could not be assigned to 'VCA' object! Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object! Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object! Mixed model equations were solved but results could not be assigned to 'VCA' object! Mixed model equations were solved but results could not be assigned to 'VCA' object! Mixed model equations were solved but results could not be assigned to 'VCA' object! [1] TRUE [1] TRUE [1] TRUE [1] TRUE [1] TRUE [1] TRUE Note: 'ddfm' set to "satterthwaite", currently option "contain" does not work for REML-estimation! Warning in lsmeans(fit.vca, var = "snp", at = list(tim = 1:4)) : Argument 'at' was not correctly specified! Neither covariables nor factor variables could be matched! Warning in lsmeans(fit.vca, var = "snp", at = list(sex = c(Male = 0.3, Female = 0.6))) : Sum of all coefficients of factor-variable 'sex' is not equal to 1! It will be skipped! Warning in lsmeans(fit.vca, var = "snp", at = list(sex = c(Male = 0.5, Female = 0.6))) : Sum of all coefficients of factor-variable 'sex' is not equal to 1! It will be skipped! Error in orderData(Data, tobj, quiet = quiet, order.data = order.data) : all(vars %in% colnames(Data)) is not TRUE Error in orderData(Data, trms, quiet = quiet, order.data = order.data) : all(vars %in% colnames(Data)) is not TRUE Mixed model equations solved locally. Results could not be assigned to object! boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! sample 1 : [1] TRUE [1] TRUE sample 2 : [1] TRUE [1] TRUE boundary (singular) fit: see help('isSingular') Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! boundary (singular) fit: see help('isSingular') sample 3 : [1] TRUE [1] TRUE sample 4 : [1] TRUE [1] TRUE Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! sample 5 : [1] TRUE [1] TRUE boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') sample 6 : [1] TRUE [1] TRUE Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! sample 7 : [1] TRUE [1] TRUE sample 8 : [1] TRUE [1] TRUE Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! sample 9 : [1] TRUE [1] TRUE sample 10 : [1] TRUE [1] TRUE boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') Error in ranef.VCA(fit) : (converted from warning) The fitted model has not been re-scaled yet! Results are likely to differ from correct results! Error in residuals.VCA(fit) : (converted from warning) The fitted model has not been re-scaled yet! Results are likely to differ from correct results! Mixed model equations were solved but results could not be assigned to 'VCA' object! Mixed model equations were solved but results could not be assigned to 'VCA' object! Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object! Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object! Mixed model equations were solved but results could not be assigned to 'VCA' object! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Some required information missing! Usually solving mixed model equations has to be done as a prerequisite! Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object! Matrices 'H' and 'Q' were comuted but could not be assigned to 'VCA' object! Mixed model equations solved locally. Results could not be assigned to object! Convert variable day from "character" to "factor"! Convert variable day from "character" to "factor"! TF075.protectedCall.anovaVCA smpl: Error in Fsweep(M, asgn = asgn) : Inverting the C Matrix failed! Double check the specified model! Are there replicates? dtld: try-error:Error in Fsweep(M, asgn = asgn) : Inverting the C Matrix failed! Double check the specified model! Are there replicates? Additional error checks: Levels of 'run' are indistinguishable from levels of 'day'! TF076.protectedCall.remlVCA smpl: Error in solve.default(VCvar[nze, nze]) : system is computationally singular: reciprocal condition number = 1.42946e-28 dtld: try-error:Error in solve.default(VCvar[nze, nze]) : system is computationally singular: reciprocal condition number = 1.42946e-28 Additional error checks: REML-estimation error! Zero variation within factor-levels of 'day:run'! TF077.protectedCall.remlMM smpl: Error in solve.default(VCvar[nze, nze]) : system is computationally singular: reciprocal condition number = 5.73223e-27 dtld: try-error:Error in solve.default(VCvar[nze, nze]) : system is computationally singular: reciprocal condition number = 5.73223e-27 Additional error checks: REML-estimation error! Zero variation within factor-levels of 'day:run'! Convert variable day from "character" to "factor"! Convert variable day from "character" to "factor"! TF078.protectedCall.anovaMM smpl: Error in Fsweep(M, asgn = asgn) : Inverting the C Matrix failed! Double check the specified model! Are there replicates? dtld: try-error:Error in Fsweep(M, asgn = asgn) : Inverting the C Matrix failed! Double check the specified model! Are there replicates? Additional error checks: Levels of 'run' are indistinguishable from levels of 'day'! Convert variable day from "character" to "factor"! Convert variable day from "character" to "factor"! TF079.protectedCall.fitVCA.anova smpl: Error in Fsweep(M, asgn = asgn) : Inverting the C Matrix failed! Double check the specified model! Are there replicates? dtld: try-error:Error in Fsweep(M, asgn = asgn) : Inverting the C Matrix failed! Double check the specified model! Are there replicates? Additional error checks: Levels of 'run' are indistinguishable from levels of 'day'! TF080.protectedCall.fitVCA.reml smpl: Error in solve.default(VCvar[nze, nze]) : system is computationally singular: reciprocal condition number = 1.09583e-28 dtld: try-error:Error in solve.default(VCvar[nze, nze]) : system is computationally singular: reciprocal condition number = 1.09583e-28 Additional error checks: REML-estimation error! Zero variation within factor-levels of 'day:run'! Convert variable day from "character" to "factor"! Convert variable day from "character" to "factor"! TF081.protectedCall.fitLMM.anova smpl: Error in Fsweep(M, asgn = asgn) : Inverting the C Matrix failed! Double check the specified model! Are there replicates? dtld: try-error:Error in Fsweep(M, asgn = asgn) : Inverting the C Matrix failed! Double check the specified model! Are there replicates? Additional error checks: Levels of 'run' are indistinguishable from levels of 'day'! TF082.protectedCall.fitLMM.remlss smpl: Error in solve.default(VCvar[nze, nze]) : system is computationally singular: reciprocal condition number = 2.66558e-27 dtld: try-error:Error in solve.default(VCvar[nze, nze]) : system is computationally singular: reciprocal condition number = 2.66558e-27 Additional error checks: REML-estimation error! Zero variation within factor-levels of 'day:run'! Mixed model equations solved locally. Results could not be assigned to object! Mixed model equations solved locally. Results could not be assigned to object! (V)ariance (C)omponent (A)nalysis Summary: ------------------------------------------ y ~ device + lot + device:lot:day + device:lot:day:run sample.1 sample.2 sample.3 sample.4 Mean 2.678798 23.7639580 0.7782802 3.405321 N 252.000000 252.0000000 252.0000000 252.000000 total_DF 27.677330 10.4631344 106.3063696 52.904536 total_CV 11.521830 4.0772765 37.7323877 8.319502 total_CV_OS_UCL 14.843153 6.4110853 42.5715597 9.921952 device_DF 2.000000 2.0000000 2.0000000 2.000000 device_CV 4.617069 2.4071231 8.0872550 3.070430 device_CV_OS_UCL 7.782026 3.9767325 14.3368560 5.223580 lot_DF 2.000000 2.0000000 2.0000000 2.000000 lot_CV 4.650544 1.8771975 0.0000000 1.594418 lot_CV_OS_UCL 7.834560 3.1320676 NA 3.013999 device:lot:day_DF 58.000000 58.0000000 58.0000000 58.000000 device:lot:day_CV 4.183296 2.3605729 0.0000000 1.870305 device:lot:day_CV_OS_UCL 6.070271 2.7367160 NA 3.935697 device:lot:day:run_DF 63.000000 63.0000000 63.0000000 63.000000 device:lot:day:run_CV 8.408436 0.9762235 36.7811417 7.215819 device:lot:day:run_CV_OS_UCL 9.573839 1.1640214 41.8346312 8.220375 error_DF 126.000000 126.0000000 126.0000000 126.000000 error_CV 1.267246 0.8836037 2.3403004 1.295500 error_CV_OS_UCL 1.414902 0.9865581 2.6129840 1.446447 sample.5 sample.6 sample.7 sample.8 Mean 17.462955 3.458896 48.3054268 92.725640 N 252.000000 252.000000 252.0000000 252.000000 total_DF 15.178552 93.088028 9.3223311 8.557229 total_CV 4.488937 8.087736 4.4752154 4.506293 total_CV_OS_UCL 6.435376 9.206565 7.2817636 7.536043 device_DF 2.000000 2.000000 2.0000000 2.000000 device_CV 2.126569 2.134276 2.3280878 1.989328 device_CV_OS_UCL 3.536592 3.713031 3.8487385 3.301919 lot_DF 2.000000 2.000000 2.0000000 2.000000 lot_CV 2.234642 0.000000 2.6356079 2.923038 lot_CV_OS_UCL 3.708641 NA 4.3416471 4.799338 device:lot:day_DF 58.000000 58.000000 58.0000000 58.000000 device:lot:day_CV 2.144759 0.000000 2.3004471 2.005682 device:lot:day_CV_OS_UCL 2.615303 NA 2.6773175 2.404009 device:lot:day:run_DF 63.000000 63.000000 63.0000000 63.000000 device:lot:day:run_CV 1.857450 7.696234 0.9147208 1.536632 device:lot:day:run_CV_OS_UCL 2.205796 8.765273 1.1543753 1.809268 error_DF 126.000000 126.000000 126.0000000 126.000000 error_CV 1.607645 1.274489 1.2378853 1.192098 error_CV_OS_UCL 1.794962 1.422988 1.3821194 1.330997 sample.9 sample.10 Mean 2.904678 23.584607 N 252.000000 252.000000 total_DF 89.602208 11.590610 total_CV 9.861496 3.972798 total_CV_OS_UCL 11.255893 6.074576 device_DF 2.000000 2.000000 device_CV 2.259144 2.131203 device_CV_OS_UCL 4.225087 3.522144 lot_DF 2.000000 2.000000 lot_CV 1.693129 2.040083 lot_CV_OS_UCL 3.456151 3.376425 device:lot:day_DF 58.000000 58.000000 device:lot:day_CV 4.701276 1.935390 device:lot:day_CV_OS_UCL 6.447736 2.306301 device:lot:day:run_DF 63.000000 63.000000 device:lot:day:run_CV 8.087492 1.307916 device:lot:day:run_CV_OS_UCL 9.210681 1.571198 error_DF 126.000000 126.000000 error_CV 1.330103 1.273885 error_CV_OS_UCL 1.485082 1.422314 (V)ariance (C)omponent (A)nalysis Summary: ------------------------------------------ y ~ device + lot + device:lot:day + device:lot:day:run sample.1 sample.2 sample.3 sample.4 Mean 2.67879779 23.7639580 0.77828016 3.40532077 N 252.00000000 252.0000000 252.00000000 252.00000000 total_DF 27.67732955 10.4631344 106.30636959 52.90453614 total_SD 0.30864653 0.9689223 0.29366369 0.28330573 total_SD_OS_UCL 0.39761806 1.5235276 0.33132600 0.33787429 total_CV 11.52183005 4.0772765 37.73238770 8.31950203 total_CV_OS_UCL 14.84315308 6.4110853 42.57155973 9.92195197 device_DF 2.00000000 2.0000000 2.00000000 2.00000000 device_SD 0.12368195 0.5720277 0.06294150 0.10455799 device_SD_OS_UCL 0.20846473 0.9450291 0.11158091 0.17787964 device_CV 4.61706933 2.4071231 8.08725495 3.07043011 device_CV_OS_UCL 7.78202561 3.9767325 14.33685599 5.22357959 lot_DF 2.00000000 2.0000000 2.00000000 2.00000000 lot_SD 0.12457866 0.4460964 0.00000000 0.05429504 lot_SD_OS_UCL 0.20987202 0.7443032 NA 0.10263632 lot_CV 4.65054364 1.8771975 0.00000000 1.59441791 lot_CV_OS_UCL 7.83455993 3.1320676 NA 3.01399865 device:lot:day_DF 58.00000000 58.0000000 58.00000000 58.00000000 device:lot:day_SD 0.11206204 0.5609655 0.00000000 0.06368988 device:lot:day_SD_OS_UCL 0.16261028 0.6503520 NA 0.13402309 device:lot:day_CV 4.18329594 2.3605729 0.00000000 1.87030474 device:lot:day_CV_OS_UCL 6.07027081 2.7367160 NA 3.93569653 device:lot:day:run_DF 63.00000000 63.0000000 63.00000000 63.00000000 device:lot:day:run_SD 0.22524501 0.2319893 0.28626033 0.24572179 device:lot:day:run_SD_OS_UCL 0.25646379 0.2766175 0.32559064 0.27993012 device:lot:day:run_CV 8.40843646 0.9762235 36.78114167 7.21581910 device:lot:day:run_CV_OS_UCL 9.57383906 1.1640214 41.83463125 8.22037450 error_DF 126.00000000 126.0000000 126.00000000 126.00000000 error_SD 0.03394697 0.2099792 0.01821409 0.04411592 error_SD_OS_UCL 0.03790235 0.2344453 0.02033634 0.04925615 error_CV 1.26724648 0.8836037 2.34030041 1.29549965 error_CV_OS_UCL 1.41490158 0.9865581 2.61298396 1.44644671 sample.5 sample.6 sample.7 sample.8 Mean 17.4629546 3.45889648 48.3054268 92.725640 N 252.0000000 252.00000000 252.0000000 252.000000 total_DF 15.1785521 93.08802820 9.3223311 8.557229 total_SD 0.7839010 0.27974643 2.1617719 4.178489 total_SD_OS_UCL 1.1238067 0.31844554 3.5174870 6.987844 total_CV 4.4889370 8.08773649 4.4752154 4.506293 total_CV_OS_UCL 6.4353756 9.20656460 7.2817636 7.536043 device_DF 2.0000000 2.00000000 2.0000000 2.000000 device_SD 0.3713618 0.07382240 1.1245928 1.844617 device_SD_OS_UCL 0.6175935 0.12842988 1.8591496 3.061726 device_CV 2.1265692 2.13427608 2.3280878 1.989328 device_CV_OS_UCL 3.5365921 3.71303059 3.8487385 3.301919 lot_DF 2.0000000 2.00000000 2.0000000 2.000000 lot_SD 0.3902345 0.00000000 1.2731416 2.710406 lot_SD_OS_UCL 0.6476383 NA 2.0972511 4.450217 lot_CV 2.2346418 0.00000000 2.6356079 2.923038 lot_CV_OS_UCL 3.7086411 NA 4.3416471 4.799338 device:lot:day_DF 58.0000000 58.00000000 58.0000000 58.000000 device:lot:day_SD 0.3745383 0.00000000 1.1112408 1.859782 device:lot:day_SD_OS_UCL 0.4567092 NA 1.2932896 2.229133 device:lot:day_CV 2.1447590 0.00000000 2.3004471 2.005682 device:lot:day_CV_OS_UCL 2.6153033 NA 2.6773175 2.404009 device:lot:day:run_DF 63.0000000 63.00000000 63.0000000 63.000000 device:lot:day:run_SD 0.3243656 0.26620478 0.4418598 1.424852 device:lot:day:run_SD_OS_UCL 0.3851972 0.30318171 0.5576259 1.677656 device:lot:day:run_CV 1.8574499 7.69623447 0.9147208 1.536632 device:lot:day:run_CV_OS_UCL 2.2057962 8.76527264 1.1543753 1.809268 error_DF 126.0000000 126.00000000 126.0000000 126.000000 error_SD 0.2807424 0.04408325 0.5979658 1.105380 error_SD_OS_UCL 0.3134535 0.04921968 0.6676387 1.234175 error_CV 1.6076452 1.27448898 1.2378853 1.192098 error_CV_OS_UCL 1.7949624 1.42298795 1.3821194 1.330997 sample.9 sample.10 Mean 2.90467770 23.5846069 N 252.00000000 252.0000000 total_DF 89.60220814 11.5906101 total_SD 0.28644468 0.9369689 total_SD_OS_UCL 0.32694742 1.4326650 total_CV 9.86149600 3.9727984 total_CV_OS_UCL 11.25589315 6.0745765 device_DF 2.00000000 2.0000000 device_SD 0.06562086 0.5026359 device_SD_OS_UCL 0.12272515 0.8306837 device_CV 2.25914424 2.1312032 device_CV_OS_UCL 4.22508664 3.5221435 lot_DF 2.00000000 2.0000000 lot_SD 0.04917994 0.4811455 lot_SD_OS_UCL 0.10039004 0.7963165 lot_CV 1.69312900 2.0400830 lot_CV_OS_UCL 3.45615065 3.3764249 device:lot:day_DF 58.00000000 58.0000000 device:lot:day_SD 0.13655690 0.4564541 device:lot:day_SD_OS_UCL 0.18728594 0.5439321 device:lot:day_CV 4.70127557 1.9353900 device:lot:day_CV_OS_UCL 6.44773581 2.3063015 device:lot:day:run_DF 63.00000000 63.0000000 device:lot:day:run_SD 0.23491556 0.3084668 device:lot:day:run_SD_OS_UCL 0.26754059 0.3705608 device:lot:day:run_CV 8.08749155 1.3079157 device:lot:day:run_CV_OS_UCL 9.21068073 1.5711977 error_DF 126.00000000 126.0000000 error_SD 0.03863520 0.3004408 error_SD_OS_UCL 0.04313684 0.3354471 error_CV 1.33010277 1.2738852 error_CV_OS_UCL 1.48508166 1.4223138 (V)ariance (C)omponent (A)nalysis Summary: ------------------------------------------ y ~ device + lot + device:lot:day + device:lot:day:run sample.1 sample.2 sample.3 sample.4 Mean 2.67879779 23.7639580 0.77828016 3.40532077 N 252.00000000 252.0000000 252.00000000 252.00000000 total_DF 27.67732955 10.4631344 106.30636959 52.90453614 total_SD 0.30864653 0.9689223 0.29366369 0.28330573 total_SD_OS_UCL 0.39761806 1.5235276 0.33132600 0.33787429 total_CV 11.52183005 4.0772765 37.73238770 8.31950203 total_CV_OS_UCL 14.84315308 6.4110853 42.57155973 9.92195197 device_DF 2.00000000 2.0000000 2.00000000 2.00000000 device_SD 0.12368195 0.5720277 0.06294150 0.10455799 device_SD_OS_UCL 0.20846473 0.9450291 0.11158091 0.17787964 device_CV 4.61706933 2.4071231 8.08725495 3.07043011 device_CV_OS_UCL 7.78202561 3.9767325 14.33685599 5.22357959 lot_DF 2.00000000 2.0000000 2.00000000 2.00000000 lot_SD 0.12457866 0.4460964 0.00000000 0.05429504 lot_SD_OS_UCL 0.20987202 0.7443032 NA 0.10263632 lot_CV 4.65054364 1.8771975 0.00000000 1.59441791 lot_CV_OS_UCL 7.83455993 3.1320676 NA 3.01399865 device:lot:day_DF 58.00000000 58.0000000 58.00000000 58.00000000 device:lot:day_SD 0.11206204 0.5609655 0.00000000 0.06368988 device:lot:day_SD_OS_UCL 0.16261028 0.6503520 NA 0.13402309 device:lot:day_CV 4.18329594 2.3605729 0.00000000 1.87030474 device:lot:day_CV_OS_UCL 6.07027081 2.7367160 NA 3.93569653 device:lot:day:run_DF 63.00000000 63.0000000 63.00000000 63.00000000 device:lot:day:run_SD 0.22524501 0.2319893 0.28626033 0.24572179 device:lot:day:run_SD_OS_UCL 0.25646379 0.2766175 0.32559064 0.27993012 device:lot:day:run_CV 8.40843646 0.9762235 36.78114167 7.21581910 device:lot:day:run_CV_OS_UCL 9.57383906 1.1640214 41.83463125 8.22037450 error_DF 126.00000000 126.0000000 126.00000000 126.00000000 error_SD 0.03394697 0.2099792 0.01821409 0.04411592 error_SD_OS_UCL 0.03790235 0.2344453 0.02033634 0.04925615 error_CV 1.26724648 0.8836037 2.34030041 1.29549965 error_CV_OS_UCL 1.41490158 0.9865581 2.61298396 1.44644671 sample.5 sample.6 sample.7 sample.8 Mean 17.4629546 3.45889648 48.3054268 92.725640 N 252.0000000 252.00000000 252.0000000 252.000000 total_DF 15.1785521 93.08802820 9.3223311 8.557229 total_SD 0.7839010 0.27974643 2.1617719 4.178489 total_SD_OS_UCL 1.1238067 0.31844554 3.5174870 6.987844 total_CV 4.4889370 8.08773649 4.4752154 4.506293 total_CV_OS_UCL 6.4353756 9.20656460 7.2817636 7.536043 device_DF 2.0000000 2.00000000 2.0000000 2.000000 device_SD 0.3713618 0.07382240 1.1245928 1.844617 device_SD_OS_UCL 0.6175935 0.12842988 1.8591496 3.061726 device_CV 2.1265692 2.13427608 2.3280878 1.989328 device_CV_OS_UCL 3.5365921 3.71303059 3.8487385 3.301919 lot_DF 2.0000000 2.00000000 2.0000000 2.000000 lot_SD 0.3902345 0.00000000 1.2731416 2.710406 lot_SD_OS_UCL 0.6476383 NA 2.0972511 4.450217 lot_CV 2.2346418 0.00000000 2.6356079 2.923038 lot_CV_OS_UCL 3.7086411 NA 4.3416471 4.799338 device:lot:day_DF 58.0000000 58.00000000 58.0000000 58.000000 device:lot:day_SD 0.3745383 0.00000000 1.1112408 1.859782 device:lot:day_SD_OS_UCL 0.4567092 NA 1.2932896 2.229133 device:lot:day_CV 2.1447590 0.00000000 2.3004471 2.005682 device:lot:day_CV_OS_UCL 2.6153033 NA 2.6773175 2.404009 device:lot:day:run_DF 63.0000000 63.00000000 63.0000000 63.000000 device:lot:day:run_SD 0.3243656 0.26620478 0.4418598 1.424852 device:lot:day:run_SD_OS_UCL 0.3851972 0.30318171 0.5576259 1.677656 device:lot:day:run_CV 1.8574499 7.69623447 0.9147208 1.536632 device:lot:day:run_CV_OS_UCL 2.2057962 8.76527264 1.1543753 1.809268 error_DF 126.0000000 126.00000000 126.0000000 126.000000 error_SD 0.2807424 0.04408325 0.5979658 1.105380 error_SD_OS_UCL 0.3134535 0.04921968 0.6676387 1.234175 error_CV 1.6076452 1.27448898 1.2378853 1.192098 error_CV_OS_UCL 1.7949624 1.42298795 1.3821194 1.330997 sample.9 sample.10 Mean 2.90467770 23.5846069 N 252.00000000 252.0000000 total_DF 89.60220814 11.5906101 total_SD 0.28644468 0.9369689 total_SD_OS_UCL 0.32694742 1.4326650 total_CV 9.86149600 3.9727984 total_CV_OS_UCL 11.25589315 6.0745765 device_DF 2.00000000 2.0000000 device_SD 0.06562086 0.5026359 device_SD_OS_UCL 0.12272515 0.8306837 device_CV 2.25914424 2.1312032 device_CV_OS_UCL 4.22508664 3.5221435 lot_DF 2.00000000 2.0000000 lot_SD 0.04917994 0.4811455 lot_SD_OS_UCL 0.10039004 0.7963165 lot_CV 1.69312900 2.0400830 lot_CV_OS_UCL 3.45615065 3.3764249 device:lot:day_DF 58.00000000 58.0000000 device:lot:day_SD 0.13655690 0.4564541 device:lot:day_SD_OS_UCL 0.18728594 0.5439321 device:lot:day_CV 4.70127557 1.9353900 device:lot:day_CV_OS_UCL 6.44773581 2.3063015 device:lot:day:run_DF 63.00000000 63.0000000 device:lot:day:run_SD 0.23491556 0.3084668 device:lot:day:run_SD_OS_UCL 0.26754059 0.3705608 device:lot:day:run_CV 8.08749155 1.3079157 device:lot:day:run_CV_OS_UCL 9.21068073 1.5711977 error_DF 126.00000000 126.0000000 error_SD 0.03863520 0.3004408 error_SD_OS_UCL 0.04313684 0.3354471 error_CV 1.33010277 1.2738852 error_CV_OS_UCL 1.48508166 1.4223138 ************************************************************************** Variance Component Analysis (VCA) - test cases defined in runit.remlMM.R. ************************************************************************** boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') Error in remlMM() : argument "form" is missing, with no default In addition: There were 16 warnings (use warnings() to see them) Error in remlMM(Data = 1) : argument "form" is missing, with no default Error in remlMM(Data = data.frame()) : argument "form" is missing, with no default Error in remlMM(Data = data.frame(y = 1:10)) : argument "form" is missing, with no default Error in orderData(Data, trms, quiet = quiet, order.data = order.data) : all(vars %in% colnames(Data)) is not TRUE Error in orderData(Data, trms, quiet = quiet, order.data = order.data) : all(vars %in% colnames(Data)) is not TRUE boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') *********************************************************************** Variance Component Analysis (VCA) - test cases for function 'remlVCA'. *********************************************************************** Error in remlVCA() : argument "form" is missing, with no default In addition: Warning messages: 1: In remlMM(y ~ day + cov + day:(run), dat1) : All values of response variable 'y' are equal! 2: In remlMM(y ~ day/(run), dat1) : All values of response variable 'y' are equal! 3: In remlMM(y ~ (day)/(run), dat1) : All values of response variable 'y' are equal! Error in remlVCA(Data = 1) : argument "form" is missing, with no default Error in remlVCA(Data = data.frame()) : argument "form" is missing, with no default Error in remlVCA(Data = data.frame(y = 1:10)) : argument "form" is missing, with no default Error in orderData(Data, trms, quiet = quiet, exclude.numeric = FALSE, : all(vars %in% colnames(Data)) is not TRUE Error in orderData(Data, trms, quiet = quiet, exclude.numeric = FALSE, : all(vars %in% colnames(Data)) is not TRUE boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') boundary (singular) fit: see help('isSingular') Warning messages: 1: In remlVCA(y ~ 1, Data = dataRS0003_1) : No random effects specified! Call function 'anovaVCA' instead! 2: In remlVCA(y ~ 1, Data = dataRS0003_2) : No random effects specified! Call function 'anovaVCA' instead! 3: In remlVCA(y ~ 1, Data = dataRS0003_3) : No random effects specified! Call function 'anovaVCA' instead! 4: In remlVCA(y ~ day, dat1) : All values of response variable 'y' are equal! 5: In remlVCA(y ~ day/run, dat1) : All values of response variable 'y' are equal! > > sInfo <- sessionInfo() > cat("Test Summary Report R-Paket VCA", paste("V", sInfo$otherPkgs[["VCA"]]$Version, sep=""), file="./VCA_UnitTest_Protocol.txt", append=FALSE) > cat("\n-------------------------------------", file="./VCA_UnitTest_Protocol.txt", append=TRUE ) > cat("\n\n\n1) Package Description:", file="./VCA_UnitTest_Protocol.txt", append=TRUE) > cat("\n-----------------------\n\n", file="./VCA_UnitTest_Protocol.txt", append=TRUE) > capture.output(print(sInfo$otherPkgs[["VCA"]]), file="./VCA_UnitTest_Protocol.txt", append=TRUE) > cat("\n\n\n2) Test Environment:", file="./VCA_UnitTest_Protocol.txt", append=TRUE) > cat("\n--------------------\n", file="./VCA_UnitTest_Protocol.txt", append=TRUE) > sinfo <- Sys.info() > snam <- names(sinfo) > for(i in 1:length(sinfo)) + { + cat(paste("\n", snam[i], paste(rep(" ", 20-nchar(snam[i])), collapse=""), sep=""),":\t", sinfo[i], file="./VCA_UnitTest_Protocol.txt", append=TRUE) + } > > cat("\n\n\n\n3) Test Protocol:", file="./VCA_UnitTest_Protocol.txt", append=TRUE) > cat("\n-----------------\n\n", file="./VCA_UnitTest_Protocol.txt", append=TRUE) > > printTextProtocol(testData, showDetails=FALSE) RUNIT TEST PROTOCOL -- Thu Mar 7 17:43:09 2024 *********************************************** Number of test functions: 179 Number of errors: 0 Number of failures: 0 1 Test Suite : VCA - 179 test functions, 0 errors, 0 failures > capture.output(printTextProtocol(testData, showDetails=TRUE), file="./VCA_UnitTest_Protocol.txt", append=TRUE) > printHTMLProtocol(testData, file="./VCA_UnitTest_Protocol.html") > > options(warn=0) > > > proc.time() user system elapsed 89.96 1.45 91.40