intermat

by Ran Gao
0th

Percentile

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

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. & 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. Communications in Statistics--Simulation and Computation, 45(8), 2744-2751.

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

corr.nn4bb, corr.nn4bn, corr.nn4on, corr.nn4pbo, corr.nn4pn, corr.nn4pp, and validation.specs.

• intermat
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)

# }

Documentation reproduced from package PoisBinOrdNor, version 1.6.1, License: GPL-2 | GPL-3

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