# mvnorm_sd: Draw a sample from a multivariate normal distribution In BSBT: The Bayesian Spatial Bradley--Terry Model

## Description

This draws a sample from a multivariate normal distribution with mean vector mu and covariance matrix Sigma. It requires the covariance matrix to be decomposed using spectral decomposition (eigen).

## Usage

 `1` ```mvnorm_sd(mu, decomp.covariance) ```

## Arguments

 `mu` The mean vector `decomp.covariance` This spectral decomposition part of the sampler. It is VU^0.5, where Sigma = VU*t(V). The required component is returned by the construct_constrained_covariance_matrix function.

## Value

a vector containing a sample from the distribution

## Examples

 ```1 2 3 4 5``` ```mu <- c(2, 1) #mean vector sigma <- matrix(c(2^2, 0.5*2*1, 0.5*2*1, 1^2), 2, 2) #covariacne matrix sigma.eigen <- eigen(sigma) decomp.covariance <- sigma.eigen\$vectors%*%diag(sqrt(sigma.eigen\$values)) f <- mvnorm_sd(mu, decomp.covariance) #draw sample ```

BSBT documentation built on March 15, 2021, 1:07 a.m.