rlognPareto

This function simulates the continuous and differentiable
version of the truncated lognormal-Pareto spliced distribution
proposed by Scollnik (2007).

Estimation of a lognormal - Generalized Pareto mixture via the Expectation-Maximization algorithm. Computation of bootstrap standard errors is supported and performed via parallel computing. Functions for random number simulation and density evaluation are also available. For more details see Bee and Santi (2025) <doi:10.48550/arXiv.2505.22507>.

Marco Bee

lognGPD

Estimation of a Lognormal - Generalized Pareto Mixture

rlognPareto function

<dl><dt>n</dt>
<dd>positive integer: number of observations sampled.</dd>
<dt>sigma</dt>
<dd>positive real: log-standard deviation of the truncated
lognormal distribution.</dd>
<dt>xmin</dt>
<dd>positive real: scale parameter of the Pareto distribution.</dd>
<dt>alphapar</dt>
<dd>positive real: shape parameterof the Pareto distribution.</dd></dl>

Arguments

Simulation of the lognormal-Pareto spliced distribution — rlognPareto

<dl>

<dt>n</dt>
<dd>positive integer: number of observations sampled.</dd>


<dt>sigma</dt>
<dd>positive real: log-standard deviation of the truncated
lognormal distribution.</dd>


<dt>xmin</dt>
<dd>positive real: scale parameter of the Pareto distribution.</dd>


<dt>alphapar</dt>
<dd>positive real: shape parameterof the Pareto distribution.</dd>

</dl>

rlognPareto: Simulation of the lognormal-Pareto spliced distribution

Description

Usage

Value

Arguments

Details

References

Examples