ParallelTestEM {LNPar} | R Documentation |
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)
[Package LNPar version 1.1.1 Index]