intermat

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

Demirtas, H. & Hedeker, D. (2011). A practical way for computing approximate lower and upper correlation bounds. American Statistician, Volume 65, No 2, 104-109. Ferrari, P.A. and Barberio, A. (2012). Simulating ordinal data. Multivariate Behavioral Research, 47(4), 566-589. Barberio, A. and Ferrari, P.A. (2014). GenOrd: Simulation of ordinal and discrete variables with given correlation matrix and marginal distributions. http://www.cran.r-project.org/web/packages/GenOrd. Demirtas, H. & Hedeker, D. (2016). Computing the point-biserial correlation under any underlying continuous distribution. Forthcoming in Communications in Statistics--Simulation and Computation.

See Also

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

Aliases
  • intermat
Examples
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 1.1, License: GPL (>= 2)

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