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Type 'q()' to quit R. > library(testthat) > library(BayesPostEst) > > test_check("BayesPostEst") Loading required package: rjags Loading required package: coda Linked to JAGS 4.3.1 Loaded modules: basemod,bugs Attaching package: 'R2jags' The following object is masked from 'package:coda': traceplot Loading required package: Rcpp Loading 'brms' package (version 2.22.0). Useful instructions can be found by typing help('brms'). A more detailed introduction to the package is available through vignette('brms_overview'). Attaching package: 'brms' The following object is masked from 'package:stats': ar Compiling Stan program... Start sampling SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000107 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.07 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: 0.195 seconds (Warm-up) Chain 1: 0.194 seconds (Sampling) Chain 1: 0.389 seconds (Total) Chain 1: SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 2). Chain 2: Chain 2: Gradient evaluation took 4e-05 seconds Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.4 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: 0.197 seconds (Warm-up) Chain 2: 0.205 seconds (Sampling) Chain 2: 0.402 seconds (Total) Chain 2: module glm loaded Compiling model graph Resolving undeclared variables Allocating nodes Graph information: Observed stochastic nodes: 500 Unobserved stochastic nodes: 5 Total graph size: 3509 Initializing model Compiling model graph Resolving undeclared variables Allocating nodes Graph information: Observed stochastic nodes: 500 Unobserved stochastic nodes: 5 Total graph size: 3015 Initializing model Compiling model graph Resolving undeclared variables Allocating nodes Graph information: Observed stochastic nodes: 500 Unobserved stochastic nodes: 3 Total graph size: 3506 Initializing model Compiling model graph Resolving undeclared variables Allocating nodes Graph information: Observed stochastic nodes: 500 Unobserved stochastic nodes: 3 Total graph size: 3506 Initializing model ## ## Markov Chain Monte Carlo Package (MCMCpack) ## Copyright (C) 2003-2025 Andrew D. Martin, Kevin M. Quinn, and Jong Hee Park ## ## Support provided by the U.S. National Science Foundation ## (Grants SES-0350646 and SES-0350613) ## Attaching package: 'MCMCpack' The following objects are masked from 'package:brms': ddirichlet, rdirichlet Loading required package: StanHeaders rstan version 2.32.7 (Stan version 2.32.2) For execution on a local, multicore CPU with excess RAM we recommend calling options(mc.cores = parallel::detectCores()). To avoid recompilation of unchanged Stan programs, we recommend calling rstan_options(auto_write = TRUE) For within-chain threading using `reduce_sum()` or `map_rect()` Stan functions, change `threads_per_chain` option: rstan_options(threads_per_chain = 1) Do not specify '-march=native' in 'LOCAL_CPPFLAGS' or a Makevars file Attaching package: 'rstan' The following object is masked from 'package:runjags': extract The following object is masked from 'package:R2jags': traceplot The following object is masked from 'package:coda': traceplot SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000432 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 4.32 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: 1.529 seconds (Warm-up) Chain 1: 1.461 seconds (Sampling) Chain 1: 2.99 seconds (Total) Chain 1: SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 2). Chain 2: Chain 2: Gradient evaluation took 0.000185 seconds Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 1.85 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: 1.477 seconds (Warm-up) Chain 2: 1.582 seconds (Sampling) Chain 2: 3.059 seconds (Total) Chain 2: SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 3). Chain 3: Chain 3: Gradient evaluation took 0.000181 seconds Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 1.81 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: 1.509 seconds (Warm-up) Chain 3: 1.291 seconds (Sampling) Chain 3: 2.8 seconds (Total) Chain 3: SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 4). Chain 4: Chain 4: Gradient evaluation took 0.000185 seconds Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 1.85 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: 1.512 seconds (Warm-up) Chain 4: 1.417 seconds (Sampling) Chain 4: 2.929 seconds (Total) Chain 4: 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()) Attaching package: 'rstanarm' The following object is masked from 'package:rstan': loo The following objects are masked from 'package:brms': dirichlet, exponential, get_y, lasso, ngrps SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000286 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.86 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: 0.826 seconds (Warm-up) Chain 1: 0.871 seconds (Sampling) Chain 1: 1.697 seconds (Total) Chain 1: SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 2). Chain 2: Chain 2: Gradient evaluation took 0.000123 seconds Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 1.23 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: 0.819 seconds (Warm-up) Chain 2: 0.841 seconds (Sampling) Chain 2: 1.66 seconds (Total) Chain 2: SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 3). Chain 3: Chain 3: Gradient evaluation took 0.00012 seconds Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 1.2 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: 0.843 seconds (Warm-up) Chain 3: 0.892 seconds (Sampling) Chain 3: 1.735 seconds (Total) Chain 3: SAMPLING FOR MODEL 'bernoulli' NOW (CHAIN 4). Chain 4: Chain 4: Gradient evaluation took 0.00012 seconds Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 1.2 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: 0.815 seconds (Warm-up) Chain 4: 0.867 seconds (Sampling) Chain 4: 1.682 seconds (Total) Chain 4: Compiling rjags model... Calling the simulation using the rjags method... Note: the model did not require adaptation Burning in the model for 1000 iterations... Running the model for 2000 iterations... Simulation complete Calculating summary statistics... Calculating the Gelman-Rubin statistic for 3 variables.... Finished running the simulation Compiling rjags model... Calling the simulation using the rjags method... Note: the model did not require adaptation Burning in the model for 4000 iterations... Running the model for 10000 iterations... Simulation complete Calculating summary statistics... Calculating the Gelman-Rubin statistic for 5 variables.... Finished running the simulation Compiling model graph Resolving undeclared variables Allocating nodes Graph information: Observed stochastic nodes: 5 Unobserved stochastic nodes: 3 Total graph size: 36 Initializing model Compiling rjags model... Calling the simulation using the rjags method... Note: the model did not require adaptation Burning in the model for 4000 iterations... Running the model for 10000 iterations... Simulation complete Calculating summary statistics... Calculating the Gelman-Rubin statistic for 5 variables.... Finished running the simulation Compiling rjags model... Calling the simulation using the rjags method... Note: the model did not require adaptation Burning in the model for 4000 iterations... Running the model for 10000 iterations... Simulation complete Calculating summary statistics... Calculating the Gelman-Rubin statistic for 5 variables.... Finished running the simulation Compiling model graph Resolving undeclared variables Allocating nodes Graph information: Observed stochastic nodes: 5 Unobserved stochastic nodes: 3 Total graph size: 36 Initializing model Compiling model graph Resolving undeclared variables Allocating nodes Graph information: Observed stochastic nodes: 5 Unobserved stochastic nodes: 3 Total graph size: 36 Initializing model Compiling model graph Resolving undeclared variables Allocating nodes Graph information: Observed stochastic nodes: 5 Unobserved stochastic nodes: 3 Total graph size: 36 Initializing model [ FAIL 0 | WARN 0 | SKIP 0 | PASS 143 ] > > proc.time() user system elapsed 89.59 5.15 233.09