multivariate: Simulate from a Multivariate Normal Distribution

In mathieucarmassi/CaliCo: Code Calibration in a Bayesian Framework

Description

The matrix decomposition is done via eigen; although a Choleski decomposition might be faster, the eigen decomposition is stabler.

Usage

multivariate(n = 1, mu, Sigma, tol = 1e-06, empirical = FALSE,
  EISPACK = FALSE)

Arguments

n	the number of samples required.
mu	a vector giving the means of the variables.
Sigma	a positive-definite symmetric matrix specifying the covariance matrix of the variables.
tol	tolerance (relative to largest variance) for numerical lack of positive-definiteness in Sigma.
empirical	logical. If true, mu and Sigma specify the empirical not population mean and covariance matrix.
EISPACK	logical: values other than FALSE are an error.

Value

If n = 1 a vector of the same length as mu, otherwise an n by length(mu) matrix with one sample in each row.

mathieucarmassi/CaliCo documentation built on Aug. 14, 2019, 11:32 a.m.