only_Z_grad: Wrapper for 'unif_grad_simp', but useful for optim where only...

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

Description

Wrapper for unif_grad_simp, but useful for optim where only update Z.

Usage

only_Z_grad(Z, pi_vals, scale_val, lambda, alpha, Y, a_seq, b_seq, sig_diag,
  likelihood = "normal", df = NULL)

Arguments

Z	A k by 1 matrix of numerics. The confounders.
pi_vals	A M vector of numerics. The mixing probs.
scale_val	A positive numeric. The variance inflation parameter.
lambda	A vector. This is a length M vector with the regularization parameters for the mixing proportions.
alpha	A matrix. This is of dimension p by k and are the coefficients to the confounding variables.
Y	A matrix of dimension p by 1. These are the observed regression coefficients of the observed 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.
sig_diag	A vector of length p containing the variances of the observations.
likelihood	Can be "normal" or "t".
df	A positive numeric. The degrees of freedom if the likelihood is t.

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