fitdGPD: Maximum likelihood estimation of the parameters of the...

In ExtremeRisks: Extreme Risk Measures

Maximum likelihood estimation of the parameters of the discrete generalized Pareto distribution

Description

Given a sample of exceedances, estimate the parameters via maximum likelihood along with 1-\alpha level confidence intervals.

Usage

fitdGPD(excess, alpha = 0.05)

Arguments

excess	vector of positive exceedances, i.e., Y - t \mid Y > t, with t being the threshold
alpha	level for confidence interval of scale and shape parameters. Default: 0.05, giving 95% confidence intervals

Value

a list with elements

• mle vector of dimension 2 containing estimated scale and shape parameters

• CI matrix of dimension 2 by 2 containing the 1-\alpha level confidence intervals for scale and shape

References

Hitz, A.S., G. Samorodnistsky and R.A. Davis (2024). Discrete Extremes, Journal of Data Science, 22(4), pp. 524-536.

Examples

fitdGPD(rpois(1000,2))

ExtremeRisks documentation built on Nov. 5, 2025, 7:05 p.m.