Simulate posterior predictive samples from a compnet model

Usage

postpredsamp(mod)

Arguments

mod: Object of class "compnet", which is created by the buildcompnet() function.

Value

A matrix of posterior predictive samples with a row for each observation and a column for each sample.

Examples


data(ex_presabs)
data(ex_traits)

# Quick demo run. Will prompt warnings.
# Run with default warmup and iter for good posterior sampling.
ex_compnet <- buildcompnet(presabs=ex_presabs, spvars_dist_int=ex_traits[c("ndtrait")], warmup=10, iter=20)
#> 
#> SAMPLING FOR MODEL 'srm_binomial' NOW (CHAIN 1).
#> Chain 1: 
#> Chain 1: Gradient evaluation took 8.1e-05 seconds
#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.81 seconds.
#> Chain 1: Adjust your expectations accordingly!
#> Chain 1: 
#> Chain 1: 
#> Chain 1: WARNING: No variance estimation is
#> Chain 1:          performed for num_warmup < 20
#> Chain 1: 
#> Chain 1: Iteration:  1 / 20 [  5%]  (Warmup)
#> Chain 1: Iteration:  2 / 20 [ 10%]  (Warmup)
#> Chain 1: Iteration:  4 / 20 [ 20%]  (Warmup)
#> Chain 1: Iteration:  6 / 20 [ 30%]  (Warmup)
#> Chain 1: Iteration:  8 / 20 [ 40%]  (Warmup)
#> Chain 1: Iteration: 10 / 20 [ 50%]  (Warmup)
#> Chain 1: Iteration: 11 / 20 [ 55%]  (Sampling)
#> Chain 1: Iteration: 12 / 20 [ 60%]  (Sampling)
#> Chain 1: Iteration: 14 / 20 [ 70%]  (Sampling)
#> Chain 1: Iteration: 16 / 20 [ 80%]  (Sampling)
#> Chain 1: Iteration: 18 / 20 [ 90%]  (Sampling)
#> Chain 1: Iteration: 20 / 20 [100%]  (Sampling)
#> Chain 1: 
#> Chain 1:  Elapsed Time: 0.019 seconds (Warm-up)
#> Chain 1:                0.046 seconds (Sampling)
#> Chain 1:                0.065 seconds (Total)
#> Chain 1: 
#> Warning: The largest R-hat is 2.12, 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
#> [1] "compnet uses Stan under the hood. You may see warnings from Stan alongside, this message. To deal with any warnings Stan might issue, Please see the links provided in Stan's output, as well as the compnet website:https://kyle-rosenblad.github.io/compnet/"
ex_compnet_pps <- postpredsamp(ex_compnet)