intermediate.corr.CC: Computes an intermediate correlation matrix for continuous...

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

Description

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

Usage

intermediate.corr.CC(n.P, n.B, n.C, 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.
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.C*n.C.

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.

Vale, C.D. and Maurelli, V.A. (1983). Simulating multivariate nonnormal distributions. Psychometrika, 48(3), 465-471.

See Also

intermediate.corr.PC, intermediate.corr.BC

Examples

## Not run: 
n.P=2
n.C=4
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)
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)

intmatCC=intermediate.corr.CC(n.P,n.B=0,n.C,coef.mat,corr.vec=NULL,corr.mat)
intmatCC

## End(Not run)

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