These intervals are often referred to as credible intervals, but we use the term uncertainty intervals to highlight the fact that wider intervals correspond to greater uncertainty. See posterior_interval.stanreg() in the rstanarm package for an example.

posterior_interval(object, ...)

# S3 method for default
posterior_interval(object, prob = 0.9, ...)

Arguments

object

The object to use.

...

Arguments passed to methods. See the methods in the rstanarm package for examples.

prob

A number \(p \in (0,1)\) indicating the desired probability mass to include in the intervals.

Value

posterior_interval() methods should return a matrix with two columns and as many rows as model parameters (or a subset of parameters specified by the user). For a given value of prob, \(p\), the columns correspond to the lower and upper \(100p\)\ have the names \(100\alpha/2\)\ \(\alpha = 1-p\). For example, if prob=0.9 is specified (a \(90\)\ "95%", respectively.

The default method just takes object to be a matrix (one column per parameter) and computes quantiles, with prob defaulting to 0.9.

See also

  • Guidelines and recommendations for developers of R packages interfacing with Stan and a demonstration getting a simple package working can be found in the vignettes included with rstantools and at mc-stan.org/rstantools/articles.

Examples

# Default method takes a numeric matrix (of posterior draws) draws <- matrix(rnorm(100 * 5), 100, 5) # fake draws colnames(draws) <- paste0("theta_", 1:5) posterior_interval(draws)
#> 5% 95% #> theta_1 -1.865365 1.683664 #> theta_2 -1.517411 1.882336 #> theta_3 -1.568718 1.618074 #> theta_4 -1.397015 1.842534 #> theta_5 -1.774352 1.521312
# Also see help("posterior_interval", package = "rstanarm")