mn4joint1condi: computes a joint distribution from a marginal and a... In rbmn: Handling Linear Gaussian Bayesian Networks

 mn4joint1condi R Documentation

computes a joint distribution from a marginal and a conditional one for multinormal distributions

Description

returns the expectation and variance of the multinormal normal distribution defined through a marginal subcomponent and a conditional distribution.

Usage

``````mn4joint1condi(lmar, lcon)
``````

Arguments

 `lmar` list defining the distribution of the marginal part with elements `mu`, its expectation, and `gamma`, its variance matrix (in fact a /mn/ object). `lcon` list defining the distribution of the conditional part (see the Details section).

Details

The conditional distribution is defined with a list with elements `a` for the constant part of the expectation; `b` for the regression coefficient part of the expectation; and `S` for the residual variance matrix.

Value

A list with elements:

 `mu` The expectation vector. `gamma` The joint variance matrix.

that is a /mn/ object.

Examples

`````` lcon <- list(a=c(D=2, E=4),
b=matrix(1:6, 2, dimnames=list(LETTERS[4:5],
LETTERS[1:3])),
S=matrix(c(1, 1, 1, 2), 2));

print8mn(mn4joint1condi(rbmn0mn.01, lcon));
``````

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