tupdate_pi: EM step to update pi

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

Description

EM step to update pi

Usage

tupdate_pi(Z_old, pi_old, sig_diag, Y, alpha, a_seq, b_seq, nu, lambda)

Arguments

Z_old	A vector of numerics. The current value of Z.
pi_old	A vector of numerics that sums to one. The current value of pi.
sig_diag	A vector of length p containing the variances of the observations.
Y	A matrix of dimension p by 1. These are the observed regression coefficients of the observed variables.
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.
nu	A positive numeric. The degrees of freedom of the t-distribution.
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.