PoisBinOrdNor (version 1.2)

intermat: 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

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.

See Also

corr.nn4bb, corr.nn4bn, corr.nn4on, corr.nn4pbo, corr.nn4pn, corr.nn4pp, and validation_specs.

Examples

Run this code
## 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)

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