mig_loo: Leave-one-out cross-validation for kernel density estimation...

In mig: Multivariate Inverse Gaussian Distribution

Leave-one-out cross-validation for kernel density estimation with MIG

Description

Given a data matrix over a half-space defined by beta, compute the log density using leave-one-out cross validation, taking in turn an observation as location vector and computing the density of the resulting mixture.

Usage

mig_loo(x, Omega, beta)

Arguments

x	n by d matrix of quantiles
Omega	d by d positive definite scale matrix \boldsymbol{\Omega}
beta	d vector \boldsymbol{\beta} defining the half-space through \boldsymbol{\beta}^{\top}\boldsymbol{\xi}>0

Value

the value of the likelihood cross-validation criterion

mig documentation built on April 11, 2025, 5:45 p.m.