E_step: E-step in the EAM algorithm as described in KMS19.

In depCensoring: Statistical Methods for Survival Data with Dependent Censoring

E-step in the EAM algorithm as described in KMS19.

Description

This function performs the estimation step in the EAM algorithm.

Usage

E_step(thetas, test.fun, dir, evaluations, verbose)

Arguments

thetas	Points at which to perform the E-step. Usually the result of the M-step.
test.fun	Function returning the test statistic, as well as the critical value.
dir	Direction in which to optimize. For finding upper bounds, set dir = 1, for finding lower bounds, set dir = -1.
evaluations	Matrix containing each point that was already evaluated, alongside the corresponding test statistic and critical value, as its rows.
verbose	Verbosity parameter.

Value

Results of the E-step.

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