estML: Maximum likelihood estimation of parameters in link function...

In szugat/predfat: What the package does (short line)

Description

Maximum likelihood estimation of parameters in link function for the exponential distribution

Usage

estML(x, t, delta, link, gradient, type = 1, start, ...)

Arguments

x	values of influental variable for the link function
t	values of dependent variable
delta	vector indicating of length length(t) indicating if the respective observation in t is completely observed (1) or censored (0)
link	a function(theta, log) used in the likelihood which is L(θ) = ∑ t * λ(x) - log(λ(x))
gradient	[function(x, theta, ...)] gradient of link function
type	[integer] if link function is not given a collection of given link function is available, see linkfun
start	starting solution for optim()
...	further paraments passed to optim()

Value

optimal solution for the parameter in the link function in optimum and estimated information matrix in I

szugat/predfat documentation built on May 31, 2019, 12:50 a.m.