# rValeMaurelli: 'rValeMaurelli' Simulate data from a multivariate nonnormal... In cbsem: Simulation, Estimation and Segmentation of Composite Based Structural Equation Models

## Description

`rValeMaurelli` Simulate data from a multivariate nonnormal distribution such that 1) Each marginal distribution has a specified skewness and kurtosis 2) The marginal variables have the correlation matrix R

## Usage

 `1` ```rValeMaurelli(n, R, Fcoef) ```

## Arguments

 `n` number of random vectors to be generated `R` desired correlation matrix of transformed variables `Fcoef` either vector with coefficents for the Fleishman transform to be applied to all variables or (nrow(R),3) matrix with different coefficients

## Value

X (n,nrow(R)) data matrix

## Examples

 ```1 2 3 4``` ```R <- matrix(c(1, 0.5, 0.3, 0.5 ,1, 0.2 , 0.3, 0.2 , 1),3,3) coef <- matrix(c( 0.90475830, 0.14721082, 0.02386092,0.78999781,0.57487681, -0.05473674,0.79338100, 0.05859729, 0.06363759 ),3,3,byrow=TRUE) V <- rValeMaurelli(50, R, coef) ```

cbsem documentation built on May 2, 2019, 5:56 a.m.