extract_theta: Extract latent process parameters and associated Bayesian...

In jrfaulkner/bnps: Shrinkage-Prior Markov Random Field Smoothing

Description

Extract theta (latent process) parameters from an object with posterior draws and associated Bayesian credible intervals.

Usage

extract_theta(mfit, obstype = "normal", alpha = 0.05)

Arguments

mfit	An object containing posterior draws from a spmrf model fit or stan model fit. The object can be of class stanfit, array, matrix, or data.frame.
obstype	Character string with the name of the probability distribution of the observations. This controls the back-transformation of the process parameters. Possible values for obstype are 'normal', 'poisson', or 'binomial', or 'coalescent'.
alpha	Controls level for 100*(1-alpha)% Bayesian credible intervals. Values must be 0 < alpha < 1.

Value

Returns a list with the posterior median and posterior (1-alpha) quantiles of the theta parameter vector.

See Also

stan, as.array.stanfit, as.matrix.stanfit, as.data.frame.stanfit, spmrf

jrfaulkner/bnps documentation built on Sept. 27, 2020, 12:34 p.m.