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.
vb_lap_global(X, Z, Y, max_iter = 1000, tol = 1e-06, a = 1, b = 10, lambda = 1)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.
Homogeneous covariates
Heterogeneous covariates
Response covariates
Maximum number of iterations, Defaut:1000
Algorithm convergence tolerance, Defaut:1e-6
A prior of Beta distribution, Defaut:1
A prior of Beta distribution, Defaut:10
A prior of Laplace distribution, Defaut:1