zzz-mvnorm: Multivariate Normal Distribution

In fMultivar: Rmetrics - Modeling of Multivariate Financial Return Distributions

Multivariate Normal Distribution

Description

Alternative density, distribution function, and random generation for the multivariate Normal distribution.

Details

The multivariate distribution functions to compute densities dmvnorm, probabilities pmvnorm, and to generate random numbers rmvnorm are available from the contributed R package mvtnorm. The function qmvnorm computes the equicoordinate quantile function of the multivariate normal distribution for arbitrary correlation matrices based on inversion of pmvnorm.

dmvnorm(x, mean, sigma, <<...>>
pmvnorm(<<...>>)
qmvnorm(p, <<...>>)
rmvnorm(n, mean, sigma, <<...>>

NOTE: The function are not builtin in the package fMultivar. Fur details we refer to the help page of mvnorm.

Author(s)

Friedrich Leisch and Fabian Scheipl.

Examples

## Not run: 
## Load Libray:
   require(mvtnorm)
   
## dmvnorm - 
   # Multivariate Normal Density Function:
   mean <- c(1, 1)
   sigma <- matrix(c(1, 0.5, 0.5, 1), ncol=2) 
   dmvnorm(x = c(0, 0),mean, sigma)
   
## dmvnorm - 
   # Across a Grid:
   x <- seq(-4, 4, length=90)
   X <- grid2d(x)
   X <- cbind(X$x, X$y) 
   # Write Density Function:
   dmvnorm. <- function(X, mean, sigma)
     matrix(apply(X, 1, dmvnorm, mean=mean, sigma=sigma), ncol=sqrt(dim(X)[1]))
   z <- dmvnorm.(X, mean, sigma)
   contour(list(x = x, y = x, z = z))
   
## qmvnorm -
   # Equicoordinate Quantile Function:
   qmvnorm(p = 0.95, sigma = diag(2), tail = "both")
   
## rmvnorm - 
   # Random Numbers:
   sigma <- matrix(c(4, 2, 2, 3), ncol=2)
   x <- rmvnorm(n = 500, mean = c(1, 2), sigma = sigma)
   colMeans(x)
   var(x)
   # Next Generation:
   x <- rmvnorm(n = 500, mean = c(1, 2), sigma = sigma, method = "chol")
   colMeans(x)
   var(x)
   plot(x, cex=0.5, pch=19, col="steelblue")

## End(Not run)

fMultivar documentation built on July 9, 2023, 3:08 p.m.