make_logistic_prior: Make a logistic prior with specified scale

In davharris/rosalia: Exact inference for small binary Markov networks

Description

Make a logistic prior with specified scale

Usage

make_logistic_prior(location = 0, scale, ...)

Arguments

location	Numeric vector; see Logistic
scale	Numeric vector; see Logistic
...	Currently not used

Value

A prior object, which is a list of two functions:

log_d	A function for calculating the log of the prior density for each element of a vector. Calculated with dlogis using log = TRUE
log_grad	A function for calculating the gradient of the log-density for each element of a vector.

See Also

make_flat_prior

Examples

p = make_logistic_prior(location = 0, scale = 2)
curve(p$log_d(x), from = -5, to = 5)
curve(p$log_grad(x), from = -5, to = 5)

davharris/rosalia documentation built on May 14, 2019, 9:29 p.m.