Package check result: OK

Changes to worse in reverse depends:

Package: censored
Check: tests
New result: ERROR
    Running ‘testthat.R’ [199s/199s]
  Running the tests in ‘tests/testthat.R’ failed.
  Complete output:
    > library(testthat)
    > library(censored)
    Loading required package: parsnip
    Loading required package: survival
    > 
    > test_check("censored")
    [ FAIL 13 | WARN 0 | SKIP 11 | PASS 609 ]
    
    ══ Skipped tests (11) ══════════════════════════════════════════════════════════
    • On CRAN (11): 'test-bag_tree-rpart.R:92:3',
      'test-proportional_hazards-glmnet.R:30:3',
      'test-proportional_hazards-glmnet.R:1081:3',
      'test-proportional_hazards-glmnet.R:1109:3',
      'test-proportional_hazards-glmnet.R:1118:3',
      'test-proportional_hazards-glmnet.R:1140:3',
      'test-proportional_hazards-glmnet.R:1247:3',
      'test-proportional_hazards-survival.R:143:3',
      'test-proportional_hazards.R:10:3',
      'test-survival_reg-flexsurvspline.R:465:3', 'test-survival_reg.R:9:3'
    
    ══ Failed tests ════════════════════════════════════════════════════════════════
    ── Error ('test-bag_tree-rpart.R:109:3'): survival predictions ─────────────────
    Error in `predict(f_fit, lung, type = "survival")`: When using `type` values of "survival" or "hazard" a numeric vector `eval_time` should also be given.
    Backtrace:
         ▆
      1. ├─testthat::expect_error(...) at test-bag_tree-rpart.R:109:3
      2. │ └─testthat:::expect_condition_matching(...)
      3. │   └─testthat:::quasi_capture(...)
      4. │     ├─testthat (local) .capture(...)
      5. │     │ └─base::withCallingHandlers(...)
      6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
      7. ├─stats::predict(f_fit, lung, type = "survival")
      8. └─parsnip::predict.model_fit(f_fit, lung, type = "survival")
      9.   └─parsnip:::check_pred_type_dots(object, type, ...)
     10.     └─cli::cli_abort(...)
     11.       └─rlang::abort(...)
    ── Error ('test-boost_tree-mboost.R:73:3'): survival predictions ───────────────
    Error in `predict(f_fit, lung, type = "survival")`: When using `type` values of "survival" or "hazard" a numeric vector `eval_time` should also be given.
    Backtrace:
         ▆
      1. ├─testthat::expect_error(...) at test-boost_tree-mboost.R:73:3
      2. │ └─testthat:::expect_condition_matching(...)
      3. │   └─testthat:::quasi_capture(...)
      4. │     ├─testthat (local) .capture(...)
      5. │     │ └─base::withCallingHandlers(...)
      6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
      7. ├─stats::predict(f_fit, lung, type = "survival")
      8. └─parsnip::predict.model_fit(f_fit, lung, type = "survival")
      9.   └─parsnip:::check_pred_type_dots(object, type, ...)
     10.     └─cli::cli_abort(...)
     11.       └─rlang::abort(...)
    ── Error ('test-decision_tree-partykit.R:76:3'): survival predictions ──────────
    Error in `predict(f_fit, lung, type = "survival")`: When using `type` values of "survival" or "hazard" a numeric vector `eval_time` should also be given.
    Backtrace:
         ▆
      1. ├─testthat::expect_error(...) at test-decision_tree-partykit.R:76:3
      2. │ └─testthat:::expect_condition_matching(...)
      3. │   └─testthat:::quasi_capture(...)
      4. │     ├─testthat (local) .capture(...)
      5. │     │ └─base::withCallingHandlers(...)
      6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
      7. ├─stats::predict(f_fit, lung, type = "survival")
      8. └─parsnip::predict.model_fit(f_fit, lung, type = "survival")
      9.   └─parsnip:::check_pred_type_dots(object, type, ...)
     10.     └─cli::cli_abort(...)
     11.       └─rlang::abort(...)
    ── Error ('test-decision_tree-rpart.R:65:3'): survival predictions ─────────────
    Error in `predict(f_fit, lung, type = "survival")`: When using `type` values of "survival" or "hazard" a numeric vector `eval_time` should also be given.
    Backtrace:
         ▆
      1. ├─testthat::expect_error(...) at test-decision_tree-rpart.R:65:3
      2. │ └─testthat:::expect_condition_matching(...)
      3. │   └─testthat:::quasi_capture(...)
      4. │     ├─testthat (local) .capture(...)
      5. │     │ └─base::withCallingHandlers(...)
      6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
      7. ├─stats::predict(f_fit, lung, type = "survival")
      8. └─parsnip::predict.model_fit(f_fit, lung, type = "survival")
      9.   └─parsnip:::check_pred_type_dots(object, type, ...)
     10.     └─cli::cli_abort(...)
     11.       └─rlang::abort(...)
    ── Error ('test-proportional_hazards-survival.R:168:3'): survival predictions without strata ──
    Error in `predict(f_fit, lung, type = "survival")`: When using `type` values of "survival" or "hazard" a numeric vector `eval_time` should also be given.
    Backtrace:
         ▆
      1. ├─testthat::expect_error(...) at test-proportional_hazards-survival.R:168:3
      2. │ └─testthat:::expect_condition_matching(...)
      3. │   └─testthat:::quasi_capture(...)
      4. │     ├─testthat (local) .capture(...)
      5. │     │ └─base::withCallingHandlers(...)
      6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
      7. ├─stats::predict(f_fit, lung, type = "survival")
      8. └─parsnip::predict.model_fit(f_fit, lung, type = "survival")
      9.   └─parsnip:::check_pred_type_dots(object, type, ...)
     10.     └─cli::cli_abort(...)
     11.       └─rlang::abort(...)
    ── Error ('test-rand_forest-aorsf.R:88:3'): survival predictions ───────────────
    Error in `predict(f_fit, lung_orsf, type = "survival")`: When using `type` values of "survival" or "hazard" a numeric vector `eval_time` should also be given.
    Backtrace:
         ▆
      1. ├─testthat::expect_error(...) at test-rand_forest-aorsf.R:88:3
      2. │ └─testthat:::expect_condition_matching(...)
      3. │   └─testthat:::quasi_capture(...)
      4. │     ├─testthat (local) .capture(...)
      5. │     │ └─base::withCallingHandlers(...)
      6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
      7. ├─stats::predict(f_fit, lung_orsf, type = "survival")
      8. └─parsnip::predict.model_fit(f_fit, lung_orsf, type = "survival")
      9.   └─parsnip:::check_pred_type_dots(object, type, ...)
     10.     └─cli::cli_abort(...)
     11.       └─rlang::abort(...)
    ── Error ('test-rand_forest-partykit.R:88:3'): survival predictions ────────────
    Error in `predict(f_fit, lung, type = "survival")`: When using `type` values of "survival" or "hazard" a numeric vector `eval_time` should also be given.
    Backtrace:
         ▆
      1. ├─testthat::expect_error(...) at test-rand_forest-partykit.R:88:3
      2. │ └─testthat:::expect_condition_matching(...)
      3. │   └─testthat:::quasi_capture(...)
      4. │     ├─testthat (local) .capture(...)
      5. │     │ └─base::withCallingHandlers(...)
      6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
      7. ├─stats::predict(f_fit, lung, type = "survival")
      8. └─parsnip::predict.model_fit(f_fit, lung, type = "survival")
      9.   └─parsnip:::check_pred_type_dots(object, type, ...)
     10.     └─cli::cli_abort(...)
     11.       └─rlang::abort(...)
    ── Error ('test-survival_reg-flexsurv.R:223:3'): quantile predictions ──────────
    Error in `p <= 1`: comparison (<=) is not possible for language types
    Backtrace:
        ▆
     1. ├─stats::predict(fit_s, new_data = bladder[1:3, ], type = "quantile") at test-survival_reg-flexsurv.R:223:3
     2. ├─parsnip::predict.model_fit(...)
     3. │ ├─parsnip:::predict_quantile(...)
     4. │ └─parsnip::predict_quantile.model_fit(...)
     5. │   └─rlang::eval_tidy(pred_call)
     6. ├─stats::predict(...)
     7. └─flexsurv:::predict.flexsurvreg(...)
    ── Error ('test-survival_reg-flexsurv.R:400:3'): `fix_xy()` works ──────────────
    Error in `predict(f_fit, new_data = lung_pred, type = "quantile", quantile = c(0.2, 
        0.8))`: The ellipses are not used to pass args to the model function's predict function. These arguments cannot be used: "bad_args"
    Backtrace:
        ▆
     1. ├─stats::predict(...) at test-survival_reg-flexsurv.R:400:3
     2. └─parsnip::predict.model_fit(...)
     3.   └─parsnip:::check_pred_type_dots(object, type, ...)
     4.     └─cli::cli_abort(...)
     5.       └─rlang::abort(...)
    ── Error ('test-survival_reg-flexsurvspline.R:213:3'): quantile predictions ────
    Error in `p <= 1`: comparison (<=) is not possible for language types
    Backtrace:
        ▆
     1. ├─stats::predict(fit_s, new_data = bladder[1:3, ], type = "quantile") at test-survival_reg-flexsurvspline.R:213:3
     2. ├─parsnip::predict.model_fit(...)
     3. │ ├─parsnip:::predict_quantile(...)
     4. │ └─parsnip::predict_quantile.model_fit(...)
     5. │   └─rlang::eval_tidy(pred_call)
     6. ├─stats::predict(...)
     7. └─flexsurv:::predict.flexsurvreg(...)
    ── Error ('test-survival_reg-flexsurvspline.R:408:3'): `fix_xy()` works ────────
    Error in `predict(f_fit, new_data = lung_pred, type = "quantile", quantile = c(0.2, 
        0.8))`: The ellipses are not used to pass args to the model function's predict function. These arguments cannot be used: "bad_args"
    Backtrace:
        ▆
     1. ├─stats::predict(...) at test-survival_reg-flexsurvspline.R:408:3
     2. └─parsnip::predict.model_fit(...)
     3.   └─parsnip:::check_pred_type_dots(object, type, ...)
     4.     └─cli::cli_abort(...)
     5.       └─rlang::abort(...)
    ── Error ('test-survival_reg-survival.R:129:3'): prediction of survival time quantile ──
    Error in `predict(res, head(lung), type = "quantile", quantile = (2:4)/5)`: The ellipses are not used to pass args to the model function's predict function. These arguments cannot be used: "bad_args"
    Backtrace:
        ▆
     1. ├─stats::predict(res, head(lung), type = "quantile", quantile = (2:4)/5) at test-survival_reg-survival.R:129:3
     2. └─parsnip::predict.model_fit(res, head(lung), type = "quantile", quantile = (2:4)/5)
     3.   └─parsnip:::check_pred_type_dots(object, type, ...)
     4.     └─cli::cli_abort(...)
     5.       └─rlang::abort(...)
    ── Error ('test-survival_reg-survival.R:212:3'): `fix_xy()` works ──────────────
    Error in `predict(f_fit, new_data = lung_pred, type = "quantile", quantile = c(0.2, 
        0.8))`: The ellipses are not used to pass args to the model function's predict function. These arguments cannot be used: "bad_args"
    Backtrace:
        ▆
     1. ├─stats::predict(...) at test-survival_reg-survival.R:212:3
     2. └─parsnip::predict.model_fit(...)
     3.   └─parsnip:::check_pred_type_dots(object, type, ...)
     4.     └─cli::cli_abort(...)
     5.       └─rlang::abort(...)
    
    [ FAIL 13 | WARN 0 | SKIP 11 | PASS 609 ]
    Error: Test failures
    Execution halted

Package: nestedmodels
Check: tests
New result: ERROR
    Running ‘testthat.R’ [17s/28s]
  Running the tests in ‘tests/testthat.R’ failed.
  Complete output:
    > # This file is part of the standard setup for testthat.
    > # It is recommended that you do not modify it.
    > #
    > # Where should you do additional test configuration?
    > # Learn more about the roles of various files in:
    > # * https://r-pkgs.org/tests.html
    > # * https://testthat.r-lib.org/reference/test_package.html#special-files
    > 
    > library(testthat)
    > library(nestedmodels)
    > 
    > test_check("nestedmodels")
    Loading required package: Matrix
    Loaded glmnet 4.1-8
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error in fit(...) : `penalty` must be a number or `NULL`, not a call.
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    Error: $ operator is invalid for atomic vectors
    [ FAIL 1 | WARN 1 | SKIP 4 | PASS 173 ]
    
    ══ Skipped tests (4) ═══════════════════════════════════════════════════════════
    • On CRAN (4): 'test-autoplot.R:20:3', 'test-fit_xy.R:39:3',
      'test-nested_model.R:24:3', 'test-step_nest.R:10:3'
    
    ══ Failed tests ════════════════════════════════════════════════════════════════
    ── Error ('test-multi_predict.R:13:3'): multi_predict.nested_model_fit works ───
    Error in `fix_predictions(pred, model_map$data)`: All of the predictions failed.
    Backtrace:
        ▆
     1. ├─base::suppressWarnings(...) at test-multi_predict.R:13:3
     2. │ └─base::withCallingHandlers(...)
     3. ├─parsnip::multi_predict(...)
     4. └─nestedmodels:::multi_predict.nested_model_fit(...)
     5.   └─nestedmodels:::fix_predictions(pred, model_map$data)
     6.     └─cli::cli_abort(c("All of the predictions failed."))
     7.       └─rlang::abort(...)
    
    [ FAIL 1 | WARN 1 | SKIP 4 | PASS 173 ]
    Deleting unused snapshots:
    • autoplot/combined-autoplot-results.svg
    Error: Test failures
    Execution halted

Package: offsetreg
Check: re-building of vignette outputs
New result: ERROR
  Error(s) in re-building vignettes:
    ...
  --- re-building ‘usage.Rmd’ using rmarkdown
  
  Quitting from lines 129-140 [glmnet-offset-fix] (usage.Rmd)
  Error: processing vignette 'usage.Rmd' failed with diagnostics:
  unused argument (call = call)
  --- failed re-building ‘usage.Rmd’
  
  SUMMARY: processing the following file failed:
    ‘usage.Rmd’
  
  Error: Vignette re-building failed.
  Execution halted

Package: offsetreg
Check: S3 generic/method consistency
New result: WARNING
  check_args:
    function(object, call)
  check_args.boost_tree_offset:
    function(object)
  
  check_args:
    function(object, call)
  check_args.poisson_reg_offset:
    function(object)
  See section ‘Generic functions and methods’ in the ‘Writing R
  Extensions’ manual.

Package: offsetreg
Check: tests
New result: ERROR
    Running ‘testthat.R’ [7s/7s]
  Running the tests in ‘tests/testthat.R’ failed.
  Complete output:
    > # This file is part of the standard setup for testthat.
    > # It is recommended that you do not modify it.
    > #
    > # Where should you do additional test configuration?
    > # Learn more about the roles of various files in:
    > # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
    > # * https://testthat.r-lib.org/articles/special-files.html
    > 
    > library(testthat)
    > library(offsetreg)
    > 
    > test_check("offsetreg")
    [ FAIL 6 | WARN 0 | SKIP 0 | PASS 32 ]
    
    ══ Failed tests ════════════════════════════════════════════════════════════════
    ── Error ('test-poisson.R:49:3'): poisson_reg_offset() works ───────────────────
    Error in `check_args.poisson_reg_offset(object, call = call)`: unused argument (call = call)
    Backtrace:
        ▆
     1. ├─generics::fit(...) at test-poisson.R:49:3
     2. └─parsnip::fit.model_spec(...)
     3.   └─parsnip:::form_form(object = object, control = control, env = eval_env)
     4.     └─parsnip::check_args(object, call = call)
    ── Error ('test-poisson.R:72:3'): poisson_reg_offset() works with recipes ──────
    Error in `check_args.poisson_reg_offset(object, call = call)`: unused argument (call = call)
    Backtrace:
         ▆
      1. ├─generics::fit(...) at test-poisson.R:72:3
      2. └─workflows:::fit.workflow(...)
      3.   └─workflows::.fit_model(workflow, control)
      4.     ├─generics::fit(action_model, workflow = workflow, control = control)
      5.     └─workflows:::fit.action_model(...)
      6.       └─workflows:::fit_from_xy(spec, mold, case_weights, control_parsnip)
      7.         ├─generics::fit_xy(...)
      8.         └─parsnip::fit_xy.model_spec(...)
      9.           └─parsnip:::xy_form(...)
     10.             └─parsnip:::form_form(...)
     11.               └─parsnip::check_args(object, call = call)
    ── Failure ('test-poisson.R:113:3'): finalize works ────────────────────────────
    Expected `fit(tune::finalize_workflow(wf, param_grid), us_deaths)` to run without any errors.
    i Actually got a <simpleError> with text:
      unused argument (call = call)
    ── Error ('test-xgboost.R:75:3'): boost_tree_offset() works ────────────────────
    Error in `check_args.boost_tree_offset(object, call = call)`: unused argument (call = call)
    Backtrace:
        ▆
     1. ├─generics::fit(...) at test-xgboost.R:75:3
     2. └─parsnip::fit.model_spec(...)
     3.   └─parsnip:::form_xy(...)
     4.     └─parsnip:::xy_xy(...)
     5.       └─parsnip::check_args(object, call = call)
    ── Error ('test-xgboost.R:97:3'): boost_tree_offset() works with recipes ───────
    Error in `check_args.boost_tree_offset(object, call = call)`: unused argument (call = call)
    Backtrace:
         ▆
      1. ├─generics::fit(...) at test-xgboost.R:97:3
      2. └─workflows:::fit.workflow(...)
      3.   └─workflows::.fit_model(workflow, control)
      4.     ├─generics::fit(action_model, workflow = workflow, control = control)
      5.     └─workflows:::fit.action_model(...)
      6.       └─workflows:::fit_from_xy(spec, mold, case_weights, control_parsnip)
      7.         ├─generics::fit_xy(...)
      8.         └─parsnip::fit_xy.model_spec(...)
      9.           └─parsnip:::xy_xy(...)
     10.             └─parsnip::check_args(object, call = call)
    ── Failure ('test-xgboost.R:137:3'): finalize works ────────────────────────────
    Expected `fit(tune::finalize_workflow(wf, param_grid), us_deaths)` to run without any errors.
    i Actually got a <simpleError> with text:
      unused argument (call = call)
    
    [ FAIL 6 | WARN 0 | SKIP 0 | PASS 32 ]
    Error: Test failures
    Execution halted