mig_kdens {mig}

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