Int.Corr.NN: Computes an intermediate correlation matrix for continuous...

In BinNonNor: Data Generation with Binary and Continuous Non-Normal Components

Description

This function computes the intermediate correlation matrix for continuous non-normal-continuous non-normal combinations as formulated in Demirtas et al. (2012).

Usage

Int.Corr.NN(n.NN, corr.vec = NULL, corr.mat = NULL, coef.mat)

Arguments

n.NN	Number of continuous non-normal variables.
corr.vec	Vector of elements below the diagonal of correlation matrix ordered columnwise.
corr.mat	Specified correlation matrix.
coef.mat	Matrix of coefficients produced from fleishman.coef.

Value

A correlation matrix of size n.NN*n.NN.

References

Demirtas, H., Hedeker, D., and Mermelstein, R.J. (2012). Simulation of massive public health data by power polynomials. Statistics in Medicine, 31(27), 3337-3346.

See Also

fleishman.coef, Tetra.Corr.BB, Biserial.Corr.BN, overall.corr.mat

Examples

n.NN=4
corr.vec=NULL
corr.mat=matrix(c(1.0,-0.3,-0.3,-0.3,-0.3,-0.3,
-0.3,1.0,-0.3,-0.3,-0.3,-0.3,
-0.3,-0.3,1.0,0.4,0.5,0.6,
-0.3,-0.3,0.4,1.0,0.7,0.8,
-0.3,-0.3,0.5,0.7,1.0,0.9,
-0.3,-0.3,0.6,0.8,0.9,1.0),6,byrow=TRUE)

coef.mat=matrix(c(
 -0.31375,  0.00000,  0.10045, -0.10448,
  0.82632,  1.08574,  1.10502,  0.98085,
  0.31375,  0.00000, -0.10045,  0.10448,
  0.02271, -0.02945, -0.04001,  0.00272),4,byrow=TRUE)

intcor.mat=Int.Corr.NN(n.NN,corr.vec=NULL,corr.mat,coef.mat) 

BinNonNor documentation built on March 22, 2021, 9:08 a.m.