Package: rdss Check: tests New result: ERROR Running ‘testthat.R’ [13s/11s] 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(rdss) > > test_check("rdss") Loading required package: Rcpp This is rstanarm version 2.32.1 - See https://mc-stan.org/rstanarm/articles/priors for changes to default priors! - Default priors may change, so it's safest to specify priors, even if equivalent to the defaults. - For execution on a local, multicore CPU with excess RAM we recommend calling options(mc.cores = parallel::detectCores()) Loading required package: randomizr Loading required package: fabricatr Loading required package: estimatr SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 2.9e-05 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.29 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 2000 [ 0%] (Warmup) Chain 1: Iteration: 200 / 2000 [ 10%] (Warmup) Chain 1: Iteration: 400 / 2000 [ 20%] (Warmup) Chain 1: Iteration: 600 / 2000 [ 30%] (Warmup) Chain 1: Iteration: 800 / 2000 [ 40%] (Warmup) Chain 1: Iteration: 1000 / 2000 [ 50%] (Warmup) Chain 1: Iteration: 1001 / 2000 [ 50%] (Sampling) Chain 1: Iteration: 1200 / 2000 [ 60%] (Sampling) Chain 1: Iteration: 1400 / 2000 [ 70%] (Sampling) Chain 1: Iteration: 1600 / 2000 [ 80%] (Sampling) Chain 1: Iteration: 1800 / 2000 [ 90%] (Sampling) Chain 1: Iteration: 2000 / 2000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 0.026 seconds (Warm-up) Chain 1: 0.028 seconds (Sampling) Chain 1: 0.054 seconds (Total) Chain 1: SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2). Chain 2: Chain 2: Gradient evaluation took 1.2e-05 seconds Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.12 seconds. Chain 2: Adjust your expectations accordingly! Chain 2: Chain 2: Chain 2: Iteration: 1 / 2000 [ 0%] (Warmup) Chain 2: Iteration: 200 / 2000 [ 10%] (Warmup) Chain 2: Iteration: 400 / 2000 [ 20%] (Warmup) Chain 2: Iteration: 600 / 2000 [ 30%] (Warmup) Chain 2: Iteration: 800 / 2000 [ 40%] (Warmup) Chain 2: Iteration: 1000 / 2000 [ 50%] (Warmup) Chain 2: Iteration: 1001 / 2000 [ 50%] (Sampling) Chain 2: Iteration: 1200 / 2000 [ 60%] (Sampling) Chain 2: Iteration: 1400 / 2000 [ 70%] (Sampling) Chain 2: Iteration: 1600 / 2000 [ 80%] (Sampling) Chain 2: Iteration: 1800 / 2000 [ 90%] (Sampling) Chain 2: Iteration: 2000 / 2000 [100%] (Sampling) Chain 2: Chain 2: Elapsed Time: 0.028 seconds (Warm-up) Chain 2: 0.027 seconds (Sampling) Chain 2: 0.055 seconds (Total) Chain 2: SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3). Chain 3: Chain 3: Gradient evaluation took 1.2e-05 seconds Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0.12 seconds. Chain 3: Adjust your expectations accordingly! Chain 3: Chain 3: Chain 3: Iteration: 1 / 2000 [ 0%] (Warmup) Chain 3: Iteration: 200 / 2000 [ 10%] (Warmup) Chain 3: Iteration: 400 / 2000 [ 20%] (Warmup) Chain 3: Iteration: 600 / 2000 [ 30%] (Warmup) Chain 3: Iteration: 800 / 2000 [ 40%] (Warmup) Chain 3: Iteration: 1000 / 2000 [ 50%] (Warmup) Chain 3: Iteration: 1001 / 2000 [ 50%] (Sampling) Chain 3: Iteration: 1200 / 2000 [ 60%] (Sampling) Chain 3: Iteration: 1400 / 2000 [ 70%] (Sampling) Chain 3: Iteration: 1600 / 2000 [ 80%] (Sampling) Chain 3: Iteration: 1800 / 2000 [ 90%] (Sampling) Chain 3: Iteration: 2000 / 2000 [100%] (Sampling) Chain 3: Chain 3: Elapsed Time: 0.029 seconds (Warm-up) Chain 3: 0.042 seconds (Sampling) Chain 3: 0.071 seconds (Total) Chain 3: SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4). Chain 4: Chain 4: Gradient evaluation took 1.2e-05 seconds Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0.12 seconds. Chain 4: Adjust your expectations accordingly! Chain 4: Chain 4: Chain 4: Iteration: 1 / 2000 [ 0%] (Warmup) Chain 4: Iteration: 200 / 2000 [ 10%] (Warmup) Chain 4: Iteration: 400 / 2000 [ 20%] (Warmup) Chain 4: Iteration: 600 / 2000 [ 30%] (Warmup) Chain 4: Iteration: 800 / 2000 [ 40%] (Warmup) Chain 4: Iteration: 1000 / 2000 [ 50%] (Warmup) Chain 4: Iteration: 1001 / 2000 [ 50%] (Sampling) Chain 4: Iteration: 1200 / 2000 [ 60%] (Sampling) Chain 4: Iteration: 1400 / 2000 [ 70%] (Sampling) Chain 4: Iteration: 1600 / 2000 [ 80%] (Sampling) Chain 4: Iteration: 1800 / 2000 [ 90%] (Sampling) Chain 4: Iteration: 2000 / 2000 [100%] (Sampling) Chain 4: Chain 4: Elapsed Time: 0.029 seconds (Warm-up) Chain 4: 0.026 seconds (Sampling) Chain 4: 0.055 seconds (Total) Chain 4: Loading required namespace: broom.mixed Attaching package: 'dplyr' The following object is masked from 'package:DeclareDesign': vars The following object is masked from 'package:testthat': matches The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union Loading required package: sandwich Loading required package: lmtest Loading required package: zoo Attaching package: 'zoo' The following objects are masked from 'package:base': as.Date, as.Date.numeric Loading required package: ggplot2 Attaching package: 'ggplot2' The following object is masked from 'package:DeclareDesign': vars Loading required package: survey Loading required package: grid Loading required package: Matrix Loading required package: survival Attaching package: 'survey' The following object is masked from 'package:graphics': dotchart cjoint: AMCE Estimator for Conjoint Experiments Version: 2.1.1 Authors: Soubhik Barari, Elissa Berwick, Jens Hainmueller, Daniel Hopkins, Sean Liu, Anton Strezhnev, Teppei Yamamoto Loading required package: metadat Loading required package: numDeriv Loading the 'metafor' package (version 4.6-0). For an introduction to the package please type: help(metafor) [ FAIL 1 | WARN 0 | SKIP 1 | PASS 7 ] ══ Skipped tests (1) ═══════════════════════════════════════════════════════════ • interference cannot be loaded (1): 'test-experiments-over-networks.R:5:3' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Failure ('test-bayesian-regression.R:22:3'): tidy_stan works ──────────────── `simulate_design(declaration_9.3, sims = 1, future.seed = FALSE)` threw an unexpected error. Message: Error in step 4 (estimator): Error in tidy.stanreg(x, conf.int = conf.int, conf.level = conf.level, : Model does not have varying ('ran_vals') or hierarchical ('ran_pars') effects. Class: simpleError/error/condition Backtrace: ▆ 1. ├─testthat::expect_error(...) at test-bayesian-regression.R:22:3 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. └─DeclareDesign::simulate_design(declaration_9.3, sims = 1, future.seed = FALSE) 8. └─base::mapply(...) 9. └─DeclareDesign (local) ``(design = dots[[1L]][[1L]], sims = dots[[2L]][[1L]], future.seed = dots[[3L]][[1L]]) 10. └─DeclareDesign:::future_lapply(...) 11. └─base::lapply(...) 12. └─DeclareDesign (local) FUN(X[[i]], ...) 13. ├─DeclareDesign:::run_design_internal(design) 14. └─DeclareDesign:::run_design_internal.design(design) 15. └─DeclareDesign:::next_step(step, current_df, i) 16. └─base::tryCatch(...) 17. └─base (local) tryCatchList(expr, classes, parentenv, handlers) 18. └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]]) 19. └─value[[3L]](cond) [ FAIL 1 | WARN 0 | SKIP 1 | PASS 7 ] Error: Test failures Execution halted