strucBayes: Local Bayesian modeling

In shariq-mohammed/stSpikeSlabEEG: Classification Models For Electroencephalography Data

Description

Local Bayesian modeling for the EEG data with structured spike and slab prior. Performs variable selection and prediction for local modeling using structured spike and slab prior.

Usage

strucBayes(
  y = NULL,
  X = NULL,
  dist.mat = NULL,
  Nmcmc = NULL,
  burnin = NULL,
  thin = NULL,
  X.test = NULL,
  v0 = 0.005,
  a1 = 5,
  a2 = 50,
  q = 10
)

Arguments

y	binary response n values
X	data tensor n x L x τ
dist.mat	distance matrix between L locations
Nmcmc	number of MCMC samples to generate
burnin	burnin samples
thin	thinning samples >0
X.test	test data m x p x tau, defaults to NULL
v0	hyperparameter v_0, defaults to 0.005
a1	hyperparameter a_1, defaults to 5
a2	hyperparameter a_2, defaults to 50
q	hyperparameter q, defaults to 10

Examples

strucBayes()

shariq-mohammed/stSpikeSlabEEG documentation built on Aug. 2, 2020, 11:44 a.m.