# zzz-mvstnorm: Obsolete Functions In fMultivar: Rmetrics - Analysing and Modeling Multivariate Financial Return Distributions

## Description

Obsolete Functions: Alternative multivariate distribution and parameter estimation functions for the skew normal and skew Student-t distribution functions.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10``` ``` dmvsnorm(x, dim=2, mu=rep(0, dim), Omega=diag(dim), alpha=rep(0, dim)) pmvsnorm(q, dim=2, mu=rep(0, dim), Omega=diag(dim), alpha=rep(0, dim)) rmvsnorm(n, dim=2, mu=rep(0, dim), Omega=diag(dim), alpha=rep(0, dim)) dmvst(x, dim=2, mu=rep(0, dim), Omega=diag(dim), alpha=rep(0, dim), df=4) pmvst(q, dim=2, mu=rep(0, dim), Omega=diag(dim), alpha=rep(0, dim), df=4) rmvst(n, dim=2, mu=rep(0, dim), Omega=diag(dim), alpha=rep(0, dim), df=4) mvFit(x, method = c("snorm", "st"), fixed.df = NA, title = NULL, description = NULL, trace = FALSE) ```

## Arguments

 `x, q` the vector of quantiles, a matrix with "dim" columns. `n` the number of desired observations. `dim` the dimension, by default the bivariate case is considered where `dim=2` `mu, Omega, alpha, df` `mu` is a numeric vector of length "dim" representing the location parameter of the distribution, `Omega` is a symmetric positive-definite matrix of dimension "d" timesd "d", `alpha` is a numeric vector which regulates the the slant of the density, `df` a positive value representing the degrees of freedom. `method` selects the type of distribution function, either `"snorm"` which is the default, or `"st"`. `fixed.df` set to a positive value to keep fixed the parameter `nu` of the skew student-t distribution in the optimization process; with default value NULL, i.e. `nu` is estimated like the other parameters. `title` an optional project title. `description` an option project desctiption. `trace` a logical, should the estimation be traced? `...` arguments passed to the underlying "sn" density functions.

## Details

The former implementations have been replaced by wrpper functions calling functions from the package `"sn"`.

## Value

`dm*` gives the density, `pm*` gives the distribution function, and `rm*` generates `n` random deviates of dimension `dim`

`mvFit` returns an object of class `fDISTFEED`, see package `fBasics`.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```## Not run: ## Load Libray: require(mvtnorm) ## [dr]mvsnorm - dmvsnorm(rnorm2d(100)) rmvsnorm(100) ## [dr]mvst - dmvst(rt2d(100)) rmvst(100) ## End(Not run) ```

fMultivar documentation built on Nov. 17, 2017, 2:19 p.m.