EMalg: EM algorithm for srplv

In agathasr/srplv: Parametric models for estimating the lifetime distribution of a component from superposed renewal processes by means of latent variables.

Description

EMalg returns the maximum likelihood estimates obtained by EM algorithm.

Usage

EMalg(guess, Data, distribution, L)

Arguments

guess	The initial values for the parameters. The default is (1,1).
Data	Data in the srplv format as data_to_srplv.
distribution	The chose distribution: weibull, gamma, lnorm, llogis.
L	Number of Monte Carlo simulation.

Value

A list with the following components:

values	The values of parameters in all EM algorithm iterations.
est.par	The maximum likelihood estimates of the parameters.
max.logLik	The maximum likelihood value.
n.it	The number of EM iterations.
time	The computational time.

agathasr/srplv documentation built on May 17, 2020, 12:21 a.m.