unif_update_pi: E step in EM algorithm.

In dcgerard/succotashr: Surrogate and Confounder Correction Occuring Together with Adaptive Shrinkage

Description

E step in EM algorithm.

Usage

unif_update_pi(pi_old, Y, sig_diag, alpha, a_seq, b_seq, Z_old, lambda)

Arguments

pi_old	A vector of numerics. The old pi values.
Y	A matrix of dimension p by 1. These are the observed regression coefficients of the observed variables.
sig_diag	A vector of length p containing the variances of the observations.
alpha	A matrix. This is of dimension p by k and are the coefficients to the confounding variables.
a_seq	A vector of negative numerics containing the left endpoints of the mixing uniforms.
b_seq	A vector of positiv numerics containing the right endpoints of the mixing uniforms.
Z_old	A vector of numerics. The old confounders.
lambda	A vector. This is a length M vector with the regularization parameters for the mixing proportions.

dcgerard/succotashr documentation built on May 15, 2019, 1:25 a.m.