gpdfit

<p>A numeric vector. The sample from which to estimate the parameters.</p>

<p>Estimate the parameters \(k\) and \(\sigma\) of the generalized Pareto
distribution, given a sample \(x\).</p>

internal

Efficient approximate leave-one-out cross-validation (LOO)
using Pareto smoothed importance sampling (PSIS), a new procedure for
regularizing importance weights. As a byproduct of the calculations, we also
obtain approximate standard errors for estimated predictive errors and for
the comparison of predictive errors between models. We also compute the
widely applicable information criterion (WAIC).

Jonah Gabry

Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian
Models

gpdfit: Generalized Pareto distribution

Description

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