nimble: MultivariateNormal – R documentation

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MultivariateNormal

The Multivariate Normal Distribution

Description

Density and random generation for the multivariate normal distribution, using the Cholesky factor of either the precision matrix or the covariance matrix.

Usage

dmnorm_chol(x, mean, cholesky, prec_param = TRUE, log = FALSE)

rmnorm_chol(n = 1, mean, cholesky, prec_param = TRUE)

Arguments

`x`	vector of values.
`mean`	vector of values giving the mean of the distribution.
`cholesky`	upper-triangular Cholesky factor of either the precision matrix (when `prec_param` is TRUE) or covariance matrix (otherwise).
`prec_param`	logical; if TRUE the Cholesky factor is that of the precision matrix; otherwise, of the covariance matrix.
`log`	logical; if TRUE, probability density is returned on the log scale.
`n`	number of observations (only `n=1` is handled currently).

Details

See Gelman et al., Appendix A or the BUGS manual for mathematical details. The rate matrix as used here is defined as the inverse of the scale matrix, S^{-1}, given in Gelman et al.

Value

dmnorm_chol gives the density and rmnorm_chol generates random deviates.

Author(s)

Christopher Paciorek

References

Gelman, A., Carlin, J.B., Stern, H.S., and Rubin, D.B. (2004) Bayesian Data Analysis, 2nd ed. Chapman and Hall/CRC.

Examples

mean <- c(-10, 0, 10)
covmat <- matrix(c(1, .9, .3, .9, 1, -0.1, .3, -0.1, 1), 3)
ch <- chol(covmat)
x <- rmnorm_chol(1, mean, ch, prec_param = FALSE)
dmnorm_chol(x, mean, ch, prec_param = FALSE)

nimble

MCMC, Particle Filtering, and Programmable Hierarchical Modeling

v0.11.0

BSD_3_clause + file LICENSE | GPL (>= 2)

Authors

Perry de Valpine [aut], Christopher Paciorek [aut, cre], Daniel Turek [aut], Nick Michaud [aut], Cliff Anderson-Bergman [aut], Fritz Obermeyer [aut], Claudia Wehrhahn Cortes [aut] (Bayesian nonparametrics system), Abel Rodrìguez [aut] (Bayesian nonparametrics system), Duncan Temple Lang [aut] (packaging configuration), Sally Paganin [aut] (reversible jump MCMC), Jagadish Babu [ctb] (code for the compilation system for an early version of NIMBLE), Lauren Ponisio [ctb] (contributions to the cross-validation code), Peter Sujan [ctb] (multivariate t distribution code)

Initial release

2021-04-16