priorT: MCMC algorithm for the estimation of local model

In shariq-mohammed/SpikeSlabEEG: Bayesian Variable Selection for EEG Data

Description

Gibbs sampling algorithm for the estiamtion of a local model

Usage

priorT(y, X, c_init, beta_init, zeta_init, nusq_init, w_init, v0, a1, a2, q,
  Nmcmc, ind)

Arguments

y	binary response correspoding to n subjects
X	data at time t - dimension n x L
c_init	initial value for c
beta_init	initial values for β
zeta_init	initial values for ζ
nusq_init	initial values for ν^2
w_init	initial value for w - the complexity parameter
v0	hyperparameter v0
a1	hyperparameter a1
a2	hyperparameter a2
q	hyperparameter q
Nmcmc	number of MCMC samples to generate
ind	indices of MCMC samples to use after burnin ad thinning

Examples

priorT()

shariq-mohammed/SpikeSlabEEG documentation built on July 21, 2020, 12:17 a.m.