tnorm_lscv: Least squares cross-validation for truncated Gaussian kernel...

In mig: Multivariate Inverse Gaussian Distribution

Least squares cross-validation for truncated Gaussian kernel density estimation

Description

Least squares cross-validation for truncated Gaussian samples.

Usage

tnorm_lscv(x, Omega, beta, xsamp, dxsamp, mckern = TRUE)

Arguments

x	n by d matrix of observations
Omega	smoothing positive-definite matrix
beta	vector of constraints for the half-space
xsamp	n by d random sample for Monte Carlo estimation of bias
dxsamp	n vector of density for the points from xsamp
mckern	logical; if TRUE, uses the kernel as sampler for Monte Carlo estimation

Value

least square criterion value

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