rmeans_mvn_chol: Generate Sample Mean Vector from the Multivariate Normal...

In jeksterslab/multiNorm: Multivariate Normal Distribution

Description

Generate Sample Mean Vector from the Multivariate Normal Distribution Using the Cholesky Decomposition

Usage

rmeans_mvn_chol(rcap, mu, sigmacap, n, varnames = NULL, list = FALSE)

Arguments

rcap	Positive integer. R variates.
mu	Numeric vector. Parameter. Mean vector \boldsymbol{μ}.
sigmacap	Numeric matrix. Parameter. Covariance matrix \boldsymbol{Σ}.
n	Positive integer. Sample size.
varnames	Character vector Optional variable names.
list	Logical. If list = TRUE, returns a list where each element is a vector of means. If list = FALSE, returns a matrix where each row is a vector of means.

Value

A list (list = TRUE) or a matrix (list = FALSE).

Dependencies

rmvn_chol()

Author(s)

Ivan Jacob Agaloos Pesigan

See Also

Other Multivariate Normal Distribution Functions: grad_l_mvn_generic(), grad_l_mvn(), hess_l_mvn_generic(), hess_l_mvn(), l_mvn_generic(), l_mvn(), mvn_theta_helper(), negl_mvn(), rmeans_mvn_chol_of_theta(), rmvn_chol_of_rhocap(), rmvn_chol_of_theta(), rmvn_chol_of_vechsrhocap(), rmvn_chol(), rvcov_mvn_chol(), rvcov_wishart_of_vechsigmacap(), rvcov_wishart()

Examples

mu <- c(0, 0)
sigmacap <- matrix(
  data = c(
    1, 0.5, 0.5, 1
  ),
  nrow = 2
)

rmeans_mvn_chol(
  rcap = 5,
  mu = mu,
  sigmacap = sigmacap,
  n = 100
)

jeksterslab/multiNorm documentation built on Dec. 20, 2021, 10:11 p.m.