| posterior_interval {rstantools} | R Documentation |
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, ...) ## Default S3 method: posterior_interval(object, prob = 0.9, ...)
object |
The object to use. |
... |
Arguments passed to methods. See the methods in the rstanarm package for examples. |
prob |
A number p (0 < p < 1) indicating the desired probability mass to include in the intervals. |
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% interval limits and
have the names 100α/2% and 100(1 - α/2)%, where
α = 1-p. For example, if prob=0.9 is specified (a
90% interval), then the column names would be "5%" and
"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.
The guidelines for developers of R packages interfacing with Stan, a
copy of which can be found in the package vignettes. See
browseVignettes("rstantools") or vignette(package =
"rstantools"). The document is also available online at the
rstantools page on the
CRAN
website.
# 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)
# Example using rstanarm package:
# posterior_interval method for 'stanreg' objects
if (require("rstanarm")) {
fit <- stan_glmer(
mpg ~ wt + am + (1|cyl),
data = mtcars,
QR = TRUE,
prior = normal(0, 1),
iter = 500 # to speed up example
)
posterior_interval(fit, prob = 0.5)
}
# Also see help("posterior_interval", package = "rstanarm")