gibbs_1sampleDAG0: Implementation of Gibbs step for one-sample DAG0

In junsoukchoi/BayesDAG0: Bayesian Differential Zero-Inflated Negative Binomial Directed Acyclic Graphs

Implementation of Gibbs step for one-sample DAG0

Description

Implementation of Gibbs step for one-sample DAG0

Usage

gibbs_1sampleDAG0(param, tuning, priors, data, temp = 1, prob_rev = 0.5)

Arguments

param	a list with each tag corresponding to a parameter name. Valid tags are 'E', 'alpha', 'beta', 'delta', 'gamma', 'psi', 'tau', and 'rho'. The value portion of each tag is the parameter values to be updated.
tuning	a list with each tag corresponding to a parameter name. Valid tags are 'E', 'E_rev', 'alpha', 'beta', 'delta', 'gamma', and 'psi'. The value portion of each tag defines the standard deviations of Normal proposal distributions for Metropolis sampler for each parameter. The tag 'E' corresponds to birth or death of an edge, while 'E_rev' indicates reversal of an edge. The value portion of both tags should consist of the standard deviations of Gaussian proposals for alpha, beta, delta, and gamma for an update of E.
priors	a list with each tag corresponding to a parameter name. Valid tags are 'psi', 'tau', and 'rho'. The value portion of each tag defines the hyperparameters for one-sample DAG0.
data	a matrix containing data.
temp	a temperature.
prob_rev	the probability of edge-reversal.

Value

a list with the tags 'param' and 'acceptance'. The value portion of the tag 'param' gives parameter values after perfomring Gibbs step for one-sample DAG0. The value portion of the tag 'acceptance' shows the acceptance indicators for alpha, beta, delta, gamma, and psi.

junsoukchoi/BayesDAG0 documentation built on Feb. 26, 2025, 2:37 p.m.