par_logn_mix_known: Estimate the parameters of a lognormal-Pareto density,...

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

Estimate the parameters of a lognormal-Pareto density, assuming a known threshold

Description

This function estimates the parameters of a Pareto and a lognormal density, assuming a known threshold.

Usage

par_logn_mix_known(y, prior1, th, alpha, mu, sigma)

Arguments

y	non-negative numerical vector: random sample from the mixture.
prior1	scalar (0<prior1<1): starting value of the prior probability.
th	positive scalar: threshold.
alpha	non-negative scalar: starting value of the Pareto shape parameter.
mu	scalar: starting value of the lognormal parameter mu.
sigma	positive scalar: starting value of the lognormal parameter sigma.

Value

A list with the following elements:

xmin: estimated threshold.

prior: estimated mixing weight.

post: matrix of posterior probabilities.

alpha: estimated Pareto shape parameter.

mu: estimated expectation of the lognormal distribution on the lognormal scale.

sigma: estimated standard deviation of the lognormal distribution on the lognormal scale.

loglik: maximized log-likelihood.

nit: number of iterations.

Examples

mixFit <- par_logn_mix_known(TN2016, .5, 4700, 3, 7, 1.2)

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