mle_truncgauss

Given a data matrix and a vector of linear constraints for the half-space,
we compute the maximum likelihood estimator of the location and scale matrix

Provides utilities for estimation for the multivariate inverse Gaussian distribution of Minami (2003) <doi:10.1081/STA-120025379>, including random vector generation and explicit estimators of the location vector and scale matrix. The package implements kernel density estimators discussed in Belzile, Desgagnes, Genest and Ouimet (2024) <doi:10.48550/arXiv.2209.04757> for smoothing multivariate data on half-spaces.

Leo Belzile

Multivariate Inverse Gaussian Distribution

Frederic Ouimet

mle_truncgauss function

<dl><dt>xdat</dt>
<dd>matrix of observations</dd>
<dt>beta</dt>
<dd>vector of constraints defining the half-space</dd></dl>

Arguments

Maximum likelihood estimation of truncated Gaussian on half space — mle_truncgauss

<dl>

<dt>xdat</dt>
<dd>matrix of observations</dd>


<dt>beta</dt>
<dd>vector of constraints defining the half-space</dd>

</dl>

mle_truncgauss: Maximum likelihood estimation of truncated Gaussian on half space

Description

Usage

Value

Arguments