mvnorm_sd: Draw a sample from a multivariate normal distribution

Description Usage Arguments Value Examples

View source: R/mcmc_functions.R

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

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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

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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.