tcensReg_gradient_sepvar_maxLik: maxLik Gradient Vector for J Independent Truncated Normal...

In tcensReg: MLE of a Truncated Normal Distribution with Censored Data

Description

maxLik Gradient Vector for J Independent Truncated Normal Random Variables with Separate Variance

Usage

tcensReg_gradient_sepvar_maxLik(
  theta,
  y,
  X,
  group,
  left_trunc = -Inf,
  v = NULL
)

Arguments

theta	Numeric vector numeric vector containing estimates of beta and log sigma
y	Numeric vector with the observed truncated and censored outcomes
X	Numeric design matrix
group	Character vector identifying the group membership for the independent truncated normal variables. This defines the J groups.
left_trunc	Numeric scalar indicating the truncation value
v	Numeric scalar indicating the censoring value

Value

Vector of gradient values with p-1 beta parameters and log sigma for the nth iterate

tcensReg documentation built on July 8, 2020, 7:17 p.m.