ECMEBoot

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.

Estimates a lognormal-Pareto mixture by means of the Expectation-Conditional-Maximization-Either algorithm and by maximizing the profile likelihood function. A likelihood ratio test for discriminating between lognormal and Pareto tail is also implemented. See Bee, M. (2022) <doi:10.1007/s11634-022-00497-4>.

Marco Bee

LNPar

Estimation and Testing for a Lognormal-Pareto Mixture

ECMEBoot function

<dl><dt>x</dt>
<dd>list: sequence of integers 1,...,K, where K is the mumber of datasets. Set x = 1 in case
of a single dataset.</dd>
<dt>y</dt>
<dd>numerical vector: observed sample.</dd>
<dt>eps</dt>
<dd>non-negative scalar: starting value of the log-expectation of the lognormal distribution on the log scale.</dd>
<dt>maxiter</dt>
<dd>non-negative integer: maximum number of iterations of the ECME algorithm.</dd></dl>

Arguments

Bootstrap standard errors for the MLEs of a lognormal-Pareto mixture — ECMEBoot

<dl>

<dt>x</dt>
<dd>list: sequence of integers 1,...,K, where K is the mumber of datasets. Set x = 1 in case
of a single dataset.</dd>


<dt>y</dt>
<dd>numerical vector: observed sample.</dd>


<dt>eps</dt>
<dd>non-negative scalar: starting value of the log-expectation of the lognormal distribution on the log scale.</dd>


<dt>maxiter</dt>
<dd>non-negative integer: maximum number of iterations of the ECME algorithm.</dd>

</dl>

ECMEBoot: Bootstrap standard errors for the MLEs of a lognormal-Pareto mixture

Description

Usage

Value

Arguments

Details