Prior distributions

Source: R/priors.R

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

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.