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Last data update: 2014.03.03

R: Computes the final intermediate correlation matrix

overall.corr.mat

R Documentation

Computes the final intermediate correlation matrix

Description

This function computes the final correlation matrix by combining pairwise intermediate correlation matrix entries for Poisson-Poisson, Poisson-binary, Poisson-continuous, binary-binary, binary-continuous, and continuous-continuous combinations. If the resulting correlation matrix is not positive definite, a nearest positive matrix will be used.

Usage

overall.corr.mat(n.P, n.B, n.C, lambda.vec = NULL, prop.vec = NULL, coef.mat = NULL, 
corr.vec = NULL, corr.mat = NULL)

Arguments

`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.
`coef.mat`	Matrix of coefficients produced from `fleishman.coef`.
`corr.vec`	Vector of elements below the diagonal of correlation matrix ordered column-wise.
`corr.mat`	Specified correlation matrix.

Value

A correlation matrix of size (n.P+N.B+n.C)*(n.P+N.B+n.C).

Examples

## Not run: 
n.P<-1
n.B<-1
n.C<-1
lambda.vec<-c(1)
prop.vec<-c(0.3)
coef.mat<-matrix(c(0,1,0,0),4,1)
corr.vec=NULL
corr.mat=matrix(c(1,0.2,0.1,0.2,1,0.5,0.1,0.5,1),3,3)

finalmat=overall.corr.mat(n.P,n.B,n.C,lambda.vec,prop.vec,coef.mat, 
corr.vec=NULL,corr.mat)
finalmat

## End(Not run)