mig_rlcv {mig}

Robust likelihood cross-validation for kernel density estimation

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_rlcv(x, beta, Omega, xsamp, dxsamp)

Arguments

x

n by d matrix of quantiles

beta

d vector \boldsymbol{\beta} defining the half-space through \boldsymbol{\beta}^{\top}\boldsymbol{\xi}>0

Omega

d by d positive definite scale matrix \boldsymbol{\Omega}

xsamp

matrix of points at which to evaluate the integral

dxsamp

density of points

Value

the value of the likelihood cross-validation criterion