ParallelTestEM: ECME-based testing for a Pareto tail

In LNPar: Estimation and Testing for a Lognormal-Pareto Mixture

ECME-based testing for a Pareto tail

Description

This function computes the bootstrap test for the null hypothesis of a pure lognormal distribution versus the alternative of a lognormal-Pareto mixture, where the parameters of the latter are estimated by means of the ECME algorithm. likelihood. Implemented via parallel computing.

Usage

ParallelTestEM(nboot, y, obsTest)

Arguments

nboot	number of bootstrap replications.
y	observed data.
obsTest	value of the test statistics computed with the data under analysis.

Value

A list with the following elements:

LR: nboot simulated values of the llr test under the null hypothesis.

pval: p-value of the test.

Examples

minRank = 90
mixFit <- LPfitEM(TN2016,1e-12,1000)
ell1 <- mixFit$loglik
estNull <- c(mean(log(TN2016)),sd(log(TN2016)))
ellNull <- sum(log(dlnorm(TN2016,estNull[1],estNull[2])))
obsTest <- 2*(ell1-ellNull)
nboot = 2
TestRes = ParallelTestEM(nboot,TN2016,obsTest)

LNPar documentation built on April 4, 2025, 5:07 a.m.