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VBMS (version 1.0.0)

vb_lap_global: Global Laplace VB

Description

A variational Bayesian algorithm is proposed for multi-source heterogeneous models under the Laplace Spike-and-Slab prior, enabling simultaneous variable selection for both homogeneous and #' heterogeneous covariates.

Usage

vb_lap_global(X, Z, Y, max_iter = 1000, tol = 1e-06, a = 1, b = 10, lambda = 1)

Value

The mean of the homogeneity coefficient:mu1; The variance of homogeneity coefficient:sigma1; Selection coefficient:gamma1; The mean of the heterogeneous coefficient:mu2; The variance of heterogeneous coefficient:sigma2; Selection heterogeneous:gamma2.

Arguments

X

Homogeneous covariates

Z

Heterogeneous covariates

Y

Response covariates

max_iter

Maximum number of iterations, Defaut:1000

tol

Algorithm convergence tolerance, Defaut:1e-6

a

A prior of Beta distribution, Defaut:1

b

A prior of Beta distribution, Defaut:10

lambda

A prior of Laplace distribution, Defaut:1