CmatStarGpois: Computes Intermediate Correlation Matrix

In RNGforGPD: Random Number Generation for Generalized Poisson Distribution

Description

CmatStarGpois computes an intermediate correlation matrix that will be used to obtain the target correlation matrix using the inverse CDF transformation method in GenMVGpois. If the intermediate correlation matrix is not positive definite, the nearest positive definite matrix is used.

Usage

CmatStarGpois(corMat, theta.vec, lambda.vec, verbose = TRUE)

Arguments

corMat	target correlation matrix.
theta.vec	rate parameters in the generalized Poisson distribution. It is assumed that the length of the vector is at least two, and each value has to be a positive number.
lambda.vec	dispersion parameters in the generalized Poisson distribution. It is assumed that the length of the vector is at least two. All lambda values have to be less than 1. For lambda < 0, lambda must be greater than or equal to -theta/4.
verbose	logical variable that determines whether to display the traces. Default is set to TRUE.

Value

Intermediate correlation matrix.

References

Yahav, I. and Shmueli, G. (2012). On generating multivariate Poisson data in management science applications. Applied Stochastic Models in Business and Industry, 28(1), 91-102.

Examples

 lambda.vec = c(-0.2, 0.2, -0.3)
 theta.vec = c(1, 3, 4)
 M = c(0.352, 0.265, 0.342)
 N = diag(3)
 N[lower.tri(N)] = M
 TV = N + t(N)
 diag(TV) = 1
 cstar = CmatStarGpois(TV, theta.vec, lambda.vec, verbose = TRUE)
 cstar

RNGforGPD documentation built on Nov. 18, 2020, 5:08 p.m.