dlognPareto: Density of the lognormal-Pareto spliced distribution

In lognGPD: Estimation of a Lognormal - Generalized Pareto Mixture

Density of the lognormal-Pareto spliced distribution

Description

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

Usage

dlognPareto(x, sigma, xmin, alpha)

Arguments

x	vector (nx1): points where the function is evaluated.
sigma	positive real: log-standard deviation of the truncated lognormal distribution.
xmin	positive real: scale parameter of the Pareto distribution.
alpha	positive real: shape parameterof the Pareto distribution.

Details

To get a continuous and differentiable density, it is necessary to enforce constraints that reduce the number of free parameters of the model; in particular, the mixing weight and the log-mean of the lognormal distirbution are functions of the reamining parameters. See Scollnik (2007) for details.

Value

ysim (n x 1) vector: numerical values of the truncated lognormal-Pareto spliced distribution at x.

References

\insertRef

scoll07lognGPD

Examples

ysim <- dlognPareto(seq(0,20,length.out=500),1,5,2)

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