See predictive_interval.stanreg() in the rstanarm package for an example.
predictive_interval(object, ...) # S3 method for default predictive_interval(object, prob = 0.9, ...)
The object to use.
Arguments passed to methods. See the methods in the rstanarm package for examples.
A number \(p \in (0,1)\) indicating the desired probability mass to include in the intervals.
predictive_interval() methods should return a matrix with two
columns and as many rows as data points being predicted. For a given value
prob, \(p\), the columns correspond to the lower and upper
\(100(1 - \alpha/2)\)\
prob=0.9 is specified (a \(90\)\
The default method just takes
object to be a matrix and computes
prob defaulting to
The rstanarm package (mc-stan.org/rstanarm) for example methods (CRAN, GitHub).
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.
# Default method takes a numeric matrix (of draws from posterior # predictive distribution) ytilde <- matrix(rnorm(100 * 5, sd = 2), 100, 5) # fake draws predictive_interval(ytilde, prob = 0.8) #> 10% 90% #> [1,] -2.544390 2.328161 #> [2,] -2.490438 2.792269 #> [3,] -2.740283 2.702532 #> [4,] -3.077965 2.483094 #> [5,] -2.264030 2.620028 # Also see help("predictive_interval", package = "rstanarm")