EMBoot: Bootstrap standard errors for the MLEs of a lognormal-GPD...

In lognGPD: Estimation of a Lognormal - Generalized Pareto Mixture

Bootstrap standard errors for the MLEs of a lognormal-GPD mixture

Description

This function draws a bootstrap sample and uses it to estimate the parameters of a lognormal-Pareto mixture distribution. Since this is typically called by LPfitEM, see the help of LPfitEM for examples.

Usage

EMBoot(x, x0, y, maxiter)

Arguments

x	list: sequence of integers 1,...,K, where K is the mumber of datasets. Set x = 1 in case of a single dataset.
x0	numerical vector (5x1): initial values of the parameters p, \mu, \sigma, \xi, \beta.
y	numerical vector: observed sample.
maxiter	non-negative integer: maximum number of iterations of the EM algorithm.

Details

At each bootstrap replication, the mixture is estimated via the EM algorithm.

Value

Estimated parameters obtained from a bootstrap sample.

lognGPD documentation built on June 8, 2025, 11:05 a.m.