rcounts.reg: Generate correlated count random variables with individual...
In corcounts: Generate correlated count random variables

Description Usage Arguments Details Value Author(s) Examples

'rcounts.reg' is used to sample high-dimensional correlated count random variables with approximate prespecified Pearson correlation and exact margins.

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rcounts.reg(N, margins, mu, phi=matrix(NA,N,length(margins)), 
            omega=matrix(NA,N,length(margins)), 
            psi=matrix(NA,N,length(margins)), corstr, corpar, conv=0.01)

`N`	number of observations to be generated per margin (should be at least 500).
`margins`	Vector of margin tokens. Its length T is the dimension. See details.
`mu`	Matrix of dimension N x T of means for the Poisson, GP, ZIP, ZIGP and NB margins.
`phi`	Matrix of dimension N x T of dispersion parameters for the GP, and ZIGP margins. For Poisson, ZIP and NB margins, an 'NA' can be provided.
`omega`	Matrix of dimension N x T of zero-inflation parameters for the ZIP and ZIGP margins. For Poisson, GP and NB margins, an 'NA' can be provided.
`psi`	Matrix of dimension N x T of size parameters for the NB margins. For Poisson, GP, ZIP and ZIGP margins, an 'NA' can be provided.
`corstr`	Correlation structure. Can be 'ex' for exchangeable, 'AR1' for AR(1) and 'unstr' for unstructured.
`corpar`	Correlation parameter. Scalar correlation for 'ex' and 'AR1' and matrix of dimension TxT for 'unstr'.
`conv`	Convergence criterion

The entries in 'margins' can be specified as 'Poi' for Poisson, 'GP' for generalized Poisson, 'ZIP' for zero-inflated Poisson, 'ZIGP' for zero-inflated generalized Poisson and 'NB' for negative-binomial.

NOTE: there is a tradeoff between too small N (decreasing accuracy of the resulting correlation) and too high N (dramatically increasing computation time).

The function will return a matrix of counts of dimension N x T.

Vinzenz Erhardt

N <- 500

# bivariate example
margins <- c("ZIGP","GP")
mu <-    matrix(runif(N*2,10,20),N,2)
phi <-   matrix(runif(N*2,1,3),N,2)
omega <- matrix(c(runif(N,0,.3),rep(NA,N)),N,2)
corstr <- "ex"
corpar <- .5
Y <- rcounts.reg(N=N, margins=margins, mu=mu, phi=phi, omega=omega, 
                 corstr=corstr, corpar=corpar)
cor(Y)