unif_int_obj: Intermediate objective function in EM.

In dcgerard/vicar: Various Ideas for Confounder Adjustment in Regression

Description

Intermediate objective function in EM.

Usage

unif_int_obj(
  z2,
  xi,
  betahat_ols,
  alpha_tilde,
  S_diag,
  a_seq,
  b_seq,
  qvals,
  degrees_freedom
)

Arguments

z2	A vector of numerics. The current values of the unobserved confounders.
xi	A positive numeric. The current value of the variance inflation factor.
betahat_ols	A vector of numerics. The OLS regression coefficients.
alpha_tilde	A matrix of numerics. The estimates of the coefficients of the confounders.
S_diag	A vector of positive numerics. The standard errors.
a_seq	A vector of numerics (usually non-positive). The lower bounds of the uniform mixing densities.
b_seq	A vector of numerics (usually non-negative). The upper bounds of the uniform mixing densities.
qvals	A matrix of non-negative numerics whose rows sum to one. The E-step proportions.
degrees_freedom	A positive scalar or a vector of positive scalars the length of betahat_ols. The degrees of freedom of the t-distribution.

Author(s)

David Gerard

dcgerard/vicar documentation built on July 7, 2021, 1:08 p.m.