priors: Prior distributions

In phcanalytics/ecmeta: Meta-Analytic Framework for Decision Making and Error Control with External Control Arms

Description

A collection of functions used to specify priors to pass to Bayesian models.

Usage

normal(mean = 0, sd = 10)

invgamma(shape = 0.001, rate = 0.001)

student_t(location = 0, scale = 25, df = 1)

uniform(min = 0, max = 1)

Arguments

mean, location	Prior for the location parameter. This typically the mean, but for a Cauchy distribution (which is a student_t with df = 1), it is the median and the mean does not exist.
sd, scale	Prior for the scale parameter, which determines the dispersion of the distribution.
shape, rate	Shape and rate parameters for the inverse gamma distribution.
min, max	Lower and upper limits of the distribution. Must be finite.

Value

A named list to be used inside ecmeta() and predict.ecmeta functions.

phcanalytics/ecmeta documentation built on Dec. 22, 2021, 7:48 a.m.