Package check result: OK Changes to worse in reverse depends: Package: ggfixest Check: tests New result: ERROR Running ‘tinytest.R’ [6s/6s] Running the tests in ‘tests/tinytest.R’ failed. Complete output: > ## Throttle CPU threads if R CMD check (for CRAN) > > if (any(grepl("_R_CHECK", names(Sys.getenv()), fixed = TRUE))) { + # fixest + if (requireNamespace("fixest", quietly = TRUE)) { + library(fixest) + setFixest_nthreads(1) + } + + # data.table + if (requireNamespace("data.table", quietly = TRUE)) { + library(data.table) + setDTthreads(1) + } + + # magick + if (requireNamespace("magick", quietly = TRUE)) { + library(magick) + magick:::magick_threads(1) + } + } Linking to ImageMagick 7.1.1.43 Enabled features: fontconfig, freetype, fftw, heic, lcms, raw, webp, x11 Disabled features: cairo, ghostscript, pango, rsvg Using 2 threads [1] 1 > > > # Run tinytest suite > > if ( requireNamespace("tinytest", quietly=TRUE) ){ + + tinytest::test_package("ggfixest") + + } Loading required package: ggplot2 test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 0 tests test_aggr_es.R................ 48 tests 33 fails 1.1s test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests test_fixest_multi.R........... 0 tests 0.8s test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests test_ggcoefplot.R............. 0 tests 0.6s test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests test_ggiplot.R................ 0 tests 1.6s test_iplot_data.R............. 0 tests test_iplot_data.R............. 0 tests test_iplot_data.R............. 0 tests test_iplot_data.R............. 0 tests test_iplot_data.R............. 0 tests test_iplot_data.R............. 0 tests test_iplot_data.R............. 0 tests test_iplot_data.R............. 0 tests test_iplot_data.R............. 0 tests test_iplot_data.R............. 0 tests test_iplot_data.R............. 22 tests 4 fails 91ms test_nthreads.R............... 0 tests test_nthreads.R............... 0 tests ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_post[[col]], aggr_post_known[[col]], tolerance = tol) diff| Expected '0.859857566528126', got '0.861259873207569' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_cum[[col]], aggr_cum_known[[col]], tolerance = tol) diff| Expected '4.29928782137735', got '4.3062994999405' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_pre[[col]], aggr_pre_known[[col]], tolerance = tol) diff| Expected '0.856196388205688', got '0.878957693450153' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_both[[col]], aggr_both_known[[col]], tolerance = tol) diff| Mean relative difference: 0.01408092 ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_diff[[col]], aggr_diff_known[[col]], tolerance = tol) diff| Expected '0.47207477585529', got '0.527379333034877' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_rhs1[[col]], aggr_rhs1_known[[col]], tolerance = tol) diff| Expected '0.856196388205688', got '0.878957693450153' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_post[[col]], aggr_post_known[[col]], tolerance = tol) diff| Expected '4.5432572498307', got '4.53585990068435' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_cum[[col]], aggr_cum_known[[col]], tolerance = tol) diff| Expected '4.54325726173313', got '4.5358597596436' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_pre[[col]], aggr_pre_known[[col]], tolerance = tol) diff| Expected '-1.37803746371061', got '-1.34235209274958' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_both[[col]], aggr_both_known[[col]], tolerance = tol) diff| Mean relative difference: 0.007275895 ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_diff[[col]], aggr_diff_known[[col]], tolerance = tol) diff| Expected '10.7746168241598', got '9.64471776495549' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_rhs1[[col]], aggr_rhs1_known[[col]], tolerance = tol) diff| Expected '-0.210081123582062', got '-0.204640906589159' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_pre[[col]], aggr_pre_known[[col]], tolerance = tol) diff| Expected '0.168191721635732', got '0.179481860308907' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_both[[col]], aggr_both_known[[col]], tolerance = tol) diff| Mean relative difference: 0.06712557 ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_rhs1[[col]], aggr_rhs1_known[[col]], tolerance = tol) diff| Expected '0.833604357936545', got '0.83785269284703' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_post[[col]], aggr_post_known[[col]], tolerance = tol) diff| Expected '17.461901741925', got '17.4112907787669' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_cum[[col]], aggr_cum_known[[col]], tolerance = tol) diff| Expected '17.4619018234198', got '17.4112898145223' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_pre[[col]], aggr_pre_known[[col]], tolerance = tol) diff| Expected '2.57182139671994', got '2.47809005231426' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_both[[col]], aggr_both_known[[col]], tolerance = tol) diff| Mean relative difference: 0.007204967 ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_diff[[col]], aggr_diff_known[[col]], tolerance = tol) diff| Expected '87.5104245518892', got '70.7107655185095' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_rhs1[[col]], aggr_rhs1_known[[col]], tolerance = tol) diff| Expected '0.262565275096028', got '0.255231476237238' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_post[[col]], aggr_post_known[[col]], tolerance = tol) diff| Expected '2.22126426072131', got '2.21851579013433' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_cum[[col]], aggr_cum_known[[col]], tolerance = tol) diff| Expected '11.1063213256822', got '11.0925786882273' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_pre[[col]], aggr_pre_known[[col]], tolerance = tol) diff| Expected '-2.85798478381758', got '-2.90259612233785' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_both[[col]], aggr_both_known[[col]], tolerance = tol) diff| Mean relative difference: 0.009324175 ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_diff[[col]], aggr_diff_known[[col]], tolerance = tol) diff| Expected '4.16117526350566', got '4.05278032325274' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_rhs1[[col]], aggr_rhs1_known[[col]], tolerance = tol) diff| Expected '-1.85798478381758', got '-1.90259612233785' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_post[[col]], aggr_post_known[[col]], tolerance = tol) diff| Expected '5.59184398518008', got '5.59459245576706' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_cum[[col]], aggr_cum_known[[col]], tolerance = tol) diff| Expected '27.9592199038248', got '27.9729625412797' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_pre[[col]], aggr_pre_known[[col]], tolerance = tol) diff| Expected '0.498243385335269', got '0.542854723855542' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_both[[col]], aggr_both_known[[col]], tolerance = tol) diff| Mean relative difference: 0.00777654 ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_diff[[col]], aggr_diff_known[[col]], tolerance = tol) diff| Expected '6.01167438087804', got '6.12006932113096' ----- FAILED[data]: test_aggr_es.R<96--104> call| expect_equivalent(aggr_rhs1[[col]], aggr_rhs1_known[[col]], tolerance = tol) diff| Expected '1.49824338533527', got '1.54285472385554' ----- FAILED[data]: test_iplot_data.R<69--73> call| expect_equivalent(iplot_data_est[[col]], iplot_data_est_known[[col]], call| --> tolerance = tol) diff| Mean relative difference: 0.0226864 ----- FAILED[data]: test_iplot_data.R<69--73> call| expect_equivalent(iplot_data_est_log[[col]], iplot_data_est_log_known[[col]], call| --> tolerance = tol) diff| Mean relative difference: 0.2264364 ----- FAILED[data]: test_iplot_data.R<69--73> call| expect_equivalent(iplot_data_est[[col]], iplot_data_est_known[[col]], call| --> tolerance = tol) diff| Mean relative difference: 0.01597973 ----- FAILED[data]: test_iplot_data.R<69--73> call| expect_equivalent(iplot_data_est_log[[col]], iplot_data_est_log_known[[col]], call| --> tolerance = tol) diff| Mean relative difference: 0.09714743 Error: 37 out of 70 tests failed Execution halted Package: summclust Check: tests New result: ERROR Running ‘testthat.R’ [16s/17s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(summclust) > > test_check("summclust") Loading required namespace: fabricatr summclust.fixest(obj = feols_fit, cluster = ~group_id1, params = c("treatment", "log_income")) Number of observations: 95 97 99 104 98 93 116 102 100 96 Number of clusters: 7 coef tstat se p_val conf_int_l treatment 0.014634446 1.5882634 0.009214118 0.1466894 -0.006209337 log_income -0.001417457 -0.4237128 0.003345325 0.6817219 -0.008985108 conf_int_u treatment 0.035478230 log_income 0.006150194 N_G leverage partial-leverage-treatment Min. 93.00000000 0.1414602 0.09313171 1st Qu. 96.25000000 0.1655626 0.09505736 Median 98.50000000 0.1969216 0.09877701 Mean 100.00000000 0.2000000 0.10000000 3rd Qu. 101.50000000 0.2151630 0.10266611 Max. 116.00000000 0.3296761 0.11516014 coefvar 0.06497863 0.2705771 0.06531733 partial-leverage-log_income beta-treatment beta-log_income Min. 0.04745902 0.009432553 -4.418022e-03 1st Qu. 0.06474135 0.012721659 -1.545444e-03 Median 0.08748224 0.014827927 -1.478700e-03 Mean 0.10000000 0.014603939 -1.467387e-03 3rd Qu. 0.11591556 0.016141665 -9.697266e-04 Max. 0.22874955 0.020724656 4.721959e-05 coefvar 0.52899992 0.221676594 8.002307e-01 summclust.fixest(obj = feols_fit, cluster = ~group_id1, params = c("treatment", "log_income")) Number of observations: 95 97 99 104 98 93 116 102 100 96 Number of clusters: 7 coef tstat se p_val conf_int_l treatment 0.014634446 1.5882634 0.009214118 0.1466894 -0.006209337 log_income -0.001417457 -0.4237128 0.003345325 0.6817219 -0.008985108 conf_int_u treatment 0.035478230 log_income 0.006150194 N_G leverage partial-leverage-treatment Min. 93.00000000 0.1414602 0.09313171 1st Qu. 96.25000000 0.1655626 0.09505736 Median 98.50000000 0.1969216 0.09877701 Mean 100.00000000 0.2000000 0.10000000 3rd Qu. 101.50000000 0.2151630 0.10266611 Max. 116.00000000 0.3296761 0.11516014 coefvar 0.06497863 0.2705771 0.06531733 partial-leverage-log_income beta-treatment beta-log_income Min. 0.04745902 0.009432553 -4.418022e-03 1st Qu. 0.06474135 0.012721659 -1.545444e-03 Median 0.08748224 0.014827927 -1.478700e-03 Mean 0.10000000 0.014603939 -1.467387e-03 3rd Qu. 0.11591556 0.016141665 -9.697266e-04 Max. 0.22874955 0.020724656 4.721959e-05 coefvar 0.52899992 0.221676594 8.002307e-01 Loading required namespace: ggplot2 Loading required namespace: latex2exp Loading required package: zoo Attaching package: 'zoo' The following objects are masked from 'package:base': as.Date, as.Date.numeric downloading the 'nlswork' dataset. downloading the 'nlswork' dataset. NOTE: 1/1/0/0 fixed-effect singletons were removed (2 observations). NOTE: 1/1/0/0 fixed-effect singletons were removed (2 observations). NOTE: 1 observation removed because of NA values (vcov: 1). NOTE: 1 observation removed because of NA values (vcov: 1). NOTE: 1 observation removed because of NA values (RHS: 1). [ FAIL 3 | WARN 0 | SKIP 6 | PASS 111 ] ══ Skipped tests (6) ═══════════════════════════════════════════════════════════ • On CRAN (2): 'test-r-vs-stata-2.R:11:3', 'test-r-vs-stata.R:11:3' • packageVersion("sandwich") != "3.1.0" is TRUE (4): 'test-sandwich-vcovJK.R:7:3', 'test-sandwich-vcovJK.R:188:3', 'test-sandwich-vcovJK.R:368:3', 'test-sandwich-vcovJK.R:561:3' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Failure ('test-r-vs-stata.R:215:3'): test against stata - leverage, fixef absorb ── round(max(unlist(summclust_res$leverage_g)), 6) (`actual`) not equal to 20.011074 (`expected`). `actual`: 19.0 `expected`: 20.0 ── Failure ('test-r-vs-stata.R:221:3'): test against stata - leverage, fixef absorb ── round(mean(unlist(summclust_res$leverage_g)), 6) (`actual`) not equal to 5.333333 (`expected`). `actual`: 5.17 `expected`: 5.33 ── Failure ('test-r-vs-stata.R:269:3'): test against stata - leverage, fixef absorb ── round(summclust_res$coef_var_leverage_g, 6) (`actual`) not equal to 1.155829 (`expected`). `actual`: 1.138 `expected`: 1.156 [ FAIL 3 | WARN 0 | SKIP 6 | PASS 111 ] Error: Test failures Execution halted