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Last data update: 2014.03.03

R: Calculates and assembles the intermediate correlation matrix...

intermat

R Documentation

Calculates and assembles the intermediate correlation matrix entries for the multivariate normal data.

Description

This function computes and assembles the correlation entries for the intermediate multivariate normal data.

Usage

intermat(no_pois, no_bin, no_ord, no_norm, corr_mat, prop_vec_bin, prop_vec_ord,
 lam_vec, nor_mean, nor_var)

Arguments

`no_pois`	Number of the count variables.
`no_bin`	Number of the binary variables.
`no_ord`	Number of the ordinal variables.
`no_norm`	Number of the normal variables.
`corr_mat`	Pre-specified correlation matrix for the multivariate data.
`prop_vec_bin`	Vector of probabilities for the binary variables.
`prop_vec_ord`	Vector of probabilities for the ordinal variables.
`lam_vec`	Vector of rate parameters for the count variables.
`nor_mean`	Vector of means for the normal variables.
`nor_var`	Vector of variances for the normal variables.

Value

The intermediate correlation matrix that will be used later for multivariate normal data simulation.

References

Barberio, A. and Ferrari, P.A. (2015). GenOrd: Simulation of discrete random variables with given correlation matrix and marginal distributions. https://cran.r-project.org/web/packages/GenOrd/index.html.

Demirtas, H. & Hedeker, D. (2011). A practical way for computing approximate lower and upper correlation bounds. American Statistician, 65(2), 104-109.

Demirtas, H. & Hedeker, D. (2016). Computing the point-biserial correlation under any underlying continuous distribution. Forthcoming in Communications in Statistics–Simulation and Computation.

Ferrari, P.A. and Barberio, A. (2012). Simulating ordinal data. Multivariate Behavioral Research, 47(4), 566-589.

Examples

## Not run: 
num_pois<-2
num_bin<-1
num_ord<-2
num_norm<-1
lamvec=sample(10,2)
pbin=runif(1)
pord=list(c(0.3, 0.7), c(0.2, 0.3, 0.5))
nor.mean=3.1
nor.var=0.85
M=
c(-0.05, 0.26, 0.14, 0.09, 0.14, 0.12, 0.13, -0.02, 0.17, 0.29, -0.04, 0.19, 0.10, 0.35, 0.39)
N=diag(6)
N[lower.tri(N)]=M
TV=N+t(N)
diag(TV)<-1
intmat<-
intermat(num_pois,num_bin,num_ord,num_norm,corr_mat=TV,pbin,pord,lamvec,nor.mean,nor.var)


## End(Not run)