dev4mn: Computes the deviance for a sample of multinormal vector

In rbmn: Handling Linear Gaussian Bayesian Networks

Computes the deviance for a sample of multinormal vector

Description

From the n observed values of a vector of size p (Y), their expectations (EY) and the variance matrix (VY) supposed identical for all vectors, returns the deviance, i.e. -2*log(p(Y)).

Usage

dev4mn(Y, EY, VY)

Arguments

Y	Matrix nxp of the n observed values of length p.
EY	Expectation of Y (matrix nxp or vector p).
VY	Matrix of the variance of each row of Y (matrix pxp).

Details

When EY is a vector with length ncol(Y) this supposes that all observations have the same expectation.

Value

A scalar

Examples

 dev4mn(matrix(runif(3), 1), t(rbmn0mn.01$mu), rbmn0mn.01$gamma);

rbmn documentation built on July 9, 2023, 6:37 p.m.