gen.PoisBinNonNor: Simulates a sample of size n from a set of multivariate...

In PoisBinNonNor: Data Generation with Poisson, Binary and Continuous Components

Description

This function simulates a sample of size n from a set of multivariate Poisson, binary, and continuous data with pre-specified marginals and a correlation matrix.

Usage

gen.PoisBinNonNor(n, n.P, n.B, n.C, lambda.vec = NULL, prop.vec = NULL, 
mean.vec=NULL, variance.vec=NULL, coef.mat = NULL, final.corr.mat)

Arguments

n	Number of variates.
n.P	Number of Poisson variables.
n.B	Number of binary variables.
n.C	Number of continuous variables.
lambda.vec	Rate vector for Poisson variables.
prop.vec	Proportion vector for binary variables.
mean.vec	Mean vector of continuous variables.
variance.vec	Variance vector of continuous variables.
coef.mat	Matrix of coefficients produced from fleishman.coef.
final.corr.mat	Final correlation matrix produced from overall.corr.mat

Value

A matrix of size n*(n.P + n.B + n.C), of which the first n.P columns are Poisson variables, the next n.B columns are binary variables, and the last n.C columns are continuous variables.

Examples

## Not run: 
n=100000
n.P<-2
n.B<-2
n.C<-2
lambda.vec<-c(2,3)
prop.vec<-c(0.3,0.5)
mean.vec<-c(0,0)
variance.vec<-c(1,1)
coef.mat=matrix(rep(c(0,1,0,0), each=2),4,2,byrow=T)
corr.mat=matrix(0.4,6,6)
diag(corr.mat)=1
final.corr.mat=overall.corr.mat(n.P,n.B,n.C,lambda.vec,prop.vec, 
coef.mat,corr.vec=NULL,corr.mat)

mymixdata=gen.PoisBinNonNor(n,n.P,n.B,n.C,lambda.vec,prop.vec, 
mean.vec,variance.vec,coef.mat,final.corr.mat)

#Check marginals
#apply(mymixdata,2,mean)
#cor(mymixdata)

n=100000
n.P<-2
n.B<-2
n.N<-2
lambda.vec<-c(2,3)
prop.vec<-c(0.3,0.5)
mean.vec=c(1,0.5)
variance.vec=c(1,0.02777778)
skewness.vec=c(2,0)
kurtosis.vec=c(6,-0.5455)
coef.mat=fleishman.coef(2,skewness.vec, kurtosis.vec)
corr.mat=matrix(0.3,6,6)
diag(corr.mat)=1
final.corr.mat=overall.corr.mat(n.P,n.B,n.N,lambda.vec,prop.vec,
coef.mat,corr.vec=NULL,corr.mat)
mymixdata=gen.PoisBinNonNor(n,n.P,n.B,n.N,lambda.vec,prop.vec,
mean.vec, variance.vec,coef.mat,final.corr.mat)

#Check marginals
#apply(mymixdata,2,mean)[4:5] 
#apply(mymixdata,2,var)[4:5]  
#cor(mymixdata)

## End(Not run)

PoisBinNonNor documentation built on March 22, 2021, 9:07 a.m.