Gibbs.trueParam: Functions for sampling S_i from prior distribution

In JustinaXie/NDATA: Network Assisted Analysis for De novo mutations

Functions for sampling S_i from prior distribution

Description

Functions for sampling S_i from prior distribution

Usage

Gibbs.trueParam(
  true_theta_0,
  nodesNeighbor,
  w,
  W = NULL,
  mcmc_samples = 1000,
  burnin = 500,
  S_init = NULL
)

Arguments

true_theta_0	The true value of theta_0.
nodesNeighbor	Neighbors of corresponding nodes in the network.
w	The parameter in the prior for network.
W	Another way to input the weight. For internal use.
mcmc_samples	The number of iterations for mcmc.
burnin	The number of burn-ins for mcmc.
S_init	The vector of initial labels for all genes.

Value

The list containing S all mcmc samples, S_mcmc the mcmc samples after burning-in, llk the likelihood for checking convergence

JustinaXie/NDATA documentation built on May 22, 2022, 11:44 a.m.