log_prior: logarithm density for priors

In feng-li/movingknots: Efficient Bayesian multivariate surface regression

Description

A collection of log densities for common priors.

Usage

log_prior(B, priorArgs)

Arguments

B	"matrix". The paramter that need to be added with a prior. The prior density is calculated conditional on B. B should be always an one-column matrix,
priorArgs	"list". when priorArgs$prior_type: is set to "mvnorm", you have to provide priorArgs$mean: "matrix", the mean of parameter, mu0 should be always an one-column matrix; priorArgs$covariance: "matrix", the covariance matrix. A g-prior can be constructed by setting it to X'X, where X is the covariates matrix.; priorArgs$shrinkage: "numeric", the shrinkage for the covariance.

Details

The parameters after "..." should be matched exactly.

Value

"scalor". The log density of priors.

Author(s)

Feng Li, Department of Statistics, Stockholm University, Sweden.

feng-li/movingknots documentation built on March 30, 2021, 11:58 a.m.