Running examples in 'bayesbr-Ex.R' failed
The error most likely occurred in:

> ### Name: AIC_bayesbr
> ### Title: Akaike Information Criterion
> ### Aliases: AIC_bayesbr
> 
> ### ** Examples
> 
> data("CarTask",package = "bayesbr")
> 
> car_bayesbr <- bayesbr(probability ~ NFCCscale + task,
+                       data = CarTask,iter =100)

SAMPLING FOR MODEL 'bayesbr' NOW (CHAIN 1).
Chain 1: 
Chain 1: Gradient evaluation took 0.000259 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.59 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1: 
Chain 1: 
Chain 1: WARNING: There aren't enough warmup iterations to fit the
Chain 1:          three stages of adaptation as currently configured.
Chain 1:          Reducing each adaptation stage to 15%/75%/10% of
Chain 1:          the given number of warmup iterations:
Chain 1:            init_buffer = 7
Chain 1:            adapt_window = 38
Chain 1:            term_buffer = 5
Chain 1: 
Chain 1: Iteration:  1 / 100 [  1%]  (Warmup)
Chain 1: Iteration: 10 / 100 [ 10%]  (Warmup)
Chain 1: Iteration: 20 / 100 [ 20%]  (Warmup)
Chain 1: Iteration: 30 / 100 [ 30%]  (Warmup)
Chain 1: Iteration: 40 / 100 [ 40%]  (Warmup)
Chain 1: Iteration: 50 / 100 [ 50%]  (Warmup)
Chain 1: Iteration: 51 / 100 [ 51%]  (Sampling)
Chain 1: Iteration: 60 / 100 [ 60%]  (Sampling)
Chain 1: Iteration: 70 / 100 [ 70%]  (Sampling)
Chain 1: Iteration: 80 / 100 [ 80%]  (Sampling)
Chain 1: Iteration: 90 / 100 [ 90%]  (Sampling)
Chain 1: Iteration: 100 / 100 [100%]  (Sampling)
Chain 1: 
Chain 1:  Elapsed Time: 4.699 seconds (Warm-up)
Chain 1:                0.746 seconds (Sampling)
Chain 1:                5.445 seconds (Total)
Chain 1: 
Warning: There were 50 divergent transitions after warmup. See
https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
to find out why this is a problem and how to eliminate them.
Warning: Examine the pairs() plot to diagnose sampling problems

Warning: The largest R-hat is 1.86, indicating chains have not mixed.
Running the chains for more iterations may help. See
https://mc-stan.org/misc/warnings.html#r-hat
Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
Running the chains for more iterations may help. See
https://mc-stan.org/misc/warnings.html#bulk-ess
Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
Running the chains for more iterations may help. See
https://mc-stan.org/misc/warnings.html#tail-ess
Error in if (name == names_w[i]) { : 
  missing value where TRUE/FALSE needed
Calls: bayesbr -> model.bayesbr
Execution halted