likF.cmprsk.Cholesky: Wrapper implementing likelihood function using Cholesky...

In depCensoring: Statistical Methods for Survival Data with Dependent Censoring

Wrapper implementing likelihood function using Cholesky factorization.

Description

This function parametrizes the covariance matrix using its Cholesky decomposition, so that optimization of the likelihood can be done based on this parametrization, and positive-definiteness of the covariance matrix is guaranteed at each step of the optimization algorithm.

Usage

likF.cmprsk.Cholesky(par.chol, data, admin, conf, cf, eps = 0.001)

Arguments

par.chol	Vector of all second step model parameters, consisting of the regression parameters, Cholesky decomposition of the variance-covariance matrix elements and transformation parameters.
data	Data frame resulting from the 'uniformize.data.R' function.
admin	Boolean value indicating whether the data contains administrative censoring.
conf	Boolean value indicating whether the data contains confounding and hence indicating the presence of Z and W.
cf	"Control function" to be used. This can either be the (i) estimated control function, (ii) the true control function, (iii) the instrumental variable, or (iv) nothing (cf = NULL). Option (ii) is used when comparing the two-step estimator to the oracle estimator, and option (iii) is used to compare the two-step estimator with the naive estimator.
eps	Minimum value for the diagonal elements in the covariance matrix. Default is eps = 0.001.

Value

Log-likelihood evaluation of the second step.

depCensoring documentation built on April 4, 2025, 1:52 a.m.