mig_kdens: Multivariate inverse Gaussian kernel density estimator

In mig: Multivariate Inverse Gaussian Distribution

Multivariate inverse Gaussian kernel density estimator

Description

Given a matrix of new observations, compute the density of the multivariate inverse Gaussian mixture defined by assigning equal weight to each component where \boldsymbol{\xi} is the location parameter.

Usage

mig_kdens(x, newdata, Omega, beta, log = FALSE)

Arguments

x	n by d matrix of quantiles
newdata	matrix of new observations at which to evaluated the kernel density
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
log	logical; if TRUE, returns log probabilities

Value

value of the (log)-density at newdata

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