mmvtpdfC {NPflow}

C++ implementation of multivariate Normal probability density function for multiple inputs

Description

C++ implementation of multivariate Normal probability density function for multiple inputs

Usage

mmvtpdfC(x, mean, varcovM, df, Log = TRUE)

Arguments

x

data matrix of dimension p x n, p being the dimension of the data and n the number of data points.

mean

mean vectors matrix of dimension p x K, K being the number of distributions for which the density probability has to be evaluated.

varcovM

list of length K of variance-covariance matrices, each of dimensions p x p.

df

vector of length K of degree of freedom parameters.

Log

logical flag for returning the log of the probability density function. Defaults is TRUE.

Value

matrix of densities of dimension K x n.

Author(s)

Boris Hejblum

Examples

mvnpdf(x=matrix(1.96), mean=0, varcovM=diag(1), Log=FALSE)
mvtpdf(x=matrix(1.96), mean=0, varcovM=diag(1), df=10000000, Log=FALSE)
mmvtpdfC(x=matrix(1.96), mean=matrix(0), varcovM=list(diag(1)), df=10000000, Log=FALSE)

mvnpdf(x=matrix(1.96), mean=0, varcovM=diag(1))
mvtpdf(x=matrix(1.96), mean=0, varcovM=diag(1), df=10000000)
mmvtpdfC(x=matrix(1.96), mean=matrix(0), varcovM=list(diag(1)), df=10000000)

mvtpdf(x=matrix(1.96), mean=0, varcovM=diag(1), df=10)
mmvtpdfC(x=matrix(1.96), mean=matrix(0), varcovM=list(diag(1)), df=10)


if(require(microbenchmark)){
library(microbenchmark)
microbenchmark(mvtpdf(x=matrix(1.96), mean=0, varcovM=diag(1), df=1, Log=FALSE),
               mmvtpdfC(x=matrix(1.96), mean=matrix(0), varcovM=list(diag(1)),
                        df=c(1), Log=FALSE),
               times=10000L)
}else{
cat("package 'microbenchmark' not available\n")
}