CRAN Package Check Results for Package DoubleML

Last updated on 2021-04-22 18:48:32 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.2.1 10.36 313.89 324.25 NOTE
r-devel-linux-x86_64-debian-gcc 0.2.1 9.54 230.07 239.61 NOTE
r-devel-linux-x86_64-fedora-clang 0.2.1 373.22 NOTE
r-devel-linux-x86_64-fedora-gcc 0.2.1 370.54 NOTE
r-devel-windows-ix86+x86_64 0.2.1 20.00 352.00 372.00 NOTE
r-devel-windows-x86_64-gcc10-UCRT 0.2.1 NOTE
r-patched-linux-x86_64 0.2.1 9.92 295.37 305.29 OK
r-patched-solaris-x86 0.2.1 347.20 ERROR
r-release-linux-x86_64 0.2.1 9.47 298.20 307.67 OK
r-release-macos-x86_64 0.2.1 OK
r-release-windows-ix86+x86_64 0.2.1 20.00 364.00 384.00 OK
r-oldrel-macos-x86_64 0.2.1 OK
r-oldrel-windows-ix86+x86_64 0.2.1 24.00 360.00 384.00 OK

Check Details

Version: 0.2.1
Check: LazyData
Result: NOTE
     'LazyData' is specified without a 'data' directory
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-devel-windows-x86_64-gcc10-UCRT

Version: 0.2.1
Check: tests
Result: ERROR
     Running ‘testthat_regression_tests.R’ [203s/273s]
    Running the tests in ‘tests/testthat_regression_tests.R’ failed.
    Complete output:
     >
     > library("testthat")
     > library("patrick")
     > library("DoubleML")
     >
     > testthat::test_check("DoubleML")
     ══ Skipped tests ═══════════════════════════════════════════════════════════════
     ● On CRAN (4)
     ● Skip old regression tests (1)
    
     ══ Failed tests ════════════════════════════════════════════════════════════════
     ── Error (test-double_ml_iivm.R:33:3): Unit tests for IIVM: cv_glmnet_dml2_LATE_1_0 ──
     Error: 'NA' indices are not (yet?) supported for sparse Matrices
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─DoubleML:::dml_irmiv(...) test-double_ml_iivm.R:33:2
     3. └─mlr3::resample(task_p, ml_p, resampling_p, store_models = TRUE) helper-11-dml_irmiv.R:91:2
     4. └─future.apply::future_lapply(...)
     5. └─future.apply:::future_xapply(...)
     6. ├─future::value(fs)
     7. └─future:::value.list(fs)
     8. ├─future::resolve(...)
     9. └─future:::resolve.list(...)
     10. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     11. └─future:::signalConditions(...)
     ── Error (test-double_ml_irm.R:33:3): Unit tests for IRM: cv_glmnet_dml2_ATE_1_0 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─DoubleML:::dml_irm(...) test-double_ml_irm.R:33:2
     3. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) helper-10-dml_irm.R:69:2
     4. └─future.apply::future_lapply(...)
     5. └─future.apply:::future_xapply(...)
     6. ├─future::value(fs)
     7. └─future:::value.list(fs)
     8. ├─future::resolve(...)
     9. └─future:::resolve.list(...)
     10. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     11. └─future:::signalConditions(...)
     ── Error (test-double_ml_pliv.R:30:3): Unit tests for PLIV: regr.glmnet_dml2_partialling out_1 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─DoubleML:::dml_plriv(...) test-double_ml_pliv.R:30:2
     3. └─mlr3::resample(task_g, ml_g, resampling_g, store_models = TRUE) helper-09-dml_plriv.R:69:2
     4. └─future.apply::future_lapply(...)
     5. └─future.apply:::future_xapply(...)
     6. ├─future::value(fs)
     7. └─future:::value.list(fs)
     8. ├─future::resolve(...)
     9. └─future:::resolve.list(...)
     10. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     11. └─future:::signalConditions(...)
     ── Error (test-double_ml_pliv_partial_xz.R:67:3): Unit tests for PLIV: regr.cv_glmnet_dml2_partialling out_1 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlpliv_obj$fit() test-double_ml_pliv_partial_xz.R:67:2
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─private$ml_nuisance_and_score_elements_partialX(smpls, ...)
     5. └─DoubleML:::dml_cv_predict(...)
     6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     7. └─future.apply::future_lapply(...)
     8. └─future.apply:::future_xapply(...)
     9. ├─future::value(fs)
     10. └─future:::value.list(fs)
     11. ├─future::resolve(...)
     12. └─future:::resolve.list(...)
     13. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     14. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr.R:34:3): Unit tests for PLR: regr.cv_glmnet_dml2_partialling out_1 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─DoubleML:::DML(...) test-double_ml_plr.R:34:2
     3. └─DoubleML:::dml_plr(...) helper-06-DML.R:100:6
     4. └─mlr3::resample(task_g, ml_g, resampling_g, store_models = TRUE) helper-08-dml_plr.R:60:2
     5. └─future.apply::future_lapply(...)
     6. └─future.apply:::future_xapply(...)
     7. ├─future::value(fs)
     8. └─future:::value.list(fs)
     9. ├─future::resolve(...)
     10. └─future:::resolve.list(...)
     11. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     12. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr_classifier.R:48:5): Unit tests for PLR with classifier for ml_m: regr.cv_glmnet_classif.cv_glmnet_dml2_partialling out_1 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlplr_obj$fit() test-double_ml_plr_classifier.R:48:4
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr_export_preds.R:31:4): Unit tests for PLR with classifier for ml_m: regr.cv_glmnet_regr.cv_glmnet_dml2_partialling out_1 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlplr_obj$fit(store_predictions = TRUE) test-double_ml_plr_export_preds.R:31:3
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr_loaded_mlr3learner.R:53:3): Unit tests for PLR: dml1_IV-type_1 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlplr$fit() test-double_ml_plr_loaded_mlr3learner.R:53:2
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr_nonorth.R:66:3): Unit tests for PLR: regr.cv_glmnet_dml1_function (y, d, g_hat, m_hat, smpls)
     {
     u_hat = y - g_hat
     psi_a = -1 * d * d
     psi_b = d * u_hat
     psis = list(psi_a = psi_a, psi_b = psi_b)
     return(psis)
     }_3_2_1 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlplr_obj$fit() test-double_ml_plr_nonorth.R:66:2
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr_p_adjust.R:62:3): Unit tests for PLR: regr.cv_glmnet_dml1_partialling out_romano-wolf_TRUE ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlplr_obj$fit() test-double_ml_plr_p_adjust.R:62:2
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr_set_samples.R:59:3): Unit tests for PLR: regr.cv_glmnet_dml2_partialling out_1_2_1 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlplr_obj$fit() test-double_ml_plr_set_samples.R:59:2
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_set_samples.R:38:3): Unit tests for PLR: regr.cv_glmnet_dml1_IV-type_4_3_1 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─DoubleML:::DML(...) test-double_ml_set_samples.R:38:2
     3. └─DoubleML:::dml_plr(...) helper-06-DML.R:100:6
     4. └─mlr3::resample(task_g, ml_g, resampling_g, store_models = TRUE) helper-08-dml_plr.R:60:2
     5. └─future.apply::future_lapply(...)
     6. └─future.apply:::future_xapply(...)
     7. ├─future::value(fs)
     8. └─future:::value.list(fs)
     9. ├─future::resolve(...)
     10. └─future:::resolve.list(...)
     11. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     12. └─future:::signalConditions(...)
    
     [ FAIL 12 | WARN 0 | SKIP 5 | PASS 90 ]
     Error: Test failures
     Execution halted
Flavor: r-patched-solaris-x86