intermediate.corr.BO: Computes an intermediate normal correlation matrix for any...

In PoisBinOrd: Data Generation with Poisson, Binary and Ordinal Components

Description

Computes an intermediate normal correlation matrix for any combination of binary and ordinal variables before dichotomization/ordinalization given the specified correlation matrix as formulated in Ferrari and Barbiero (2012).

Usage

intermediate.corr.BO(n.B, n.O, prop.vec = NULL, prop.list = NULL, corr.vec = NULL, 
corr.mat = NULL)

Arguments

n.B	Number of binary variables.
n.O	Number of ordinal variables.
prop.vec	Probability vector for binary variables.
prop.list	A list of probability vectors for ordinal variables.
corr.vec	Vector of elements below the diagonal of correlation matrix ordered column-wise.
corr.mat	Specified correlation matrix.

Value

A correlation matrix of size (n.B+n.O)*(n.B+n.O).

References

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

Barbiero, A. and Ferrari, P.A. (2015). GenOrd: Simulation of ordinal and discrete variables with given correlation matrix and marginal distributions. http://www.cran.r-project.org/web/packages/GenOrd.

See Also

intermediate.corr.PBO

Examples

## Not run: 
n.B=1
n.O=2
prop.vec=0.7
prop.list=list(cumsum(c(0.30, 0.40)), cumsum(c(0.4, 0.2, 0.3)))
corr.mat=matrix ( c(
1.0000000, 0.1767231, 0.3006186,
0.1767231, 1.0000000, -0.139923,
0.3006186, -0.1399230, 1.0000000),3,3)
intmatBO=intermediate.corr.BO(n.B,n.O,prop.vec,prop.list,corr.vec=NULL, 
corr.mat)

n.B=1
n.O=1
prop.vec<-c(0.3)
prop.list<-list(c(0.3,0.6))
corr.mat=matrix(c(1,0.2,0.1,0.2,1,0.5,0.1,0.5,1),3,3)
intmatBO=intermediate.corr.BO(n.B,n.O,prop.vec,prop.list,corr.vec=NULL, 
corr.mat)

n.B=2
prop.vec=c(0.4,0.7)
corr.mat=matrix(c(1,-0.3,-0.3,1),2,2)
intmatBB=intermediate.corr.BO(n.B,n.O=0,prop.vec,prop.list=NULL,corr.vec=NULL, 
corr.mat)

#See Tetra.Corr.BB in R package BinNonNor 
#Tetra.Corr.BB(n.BB=2,prop.vec=c(0.4,0.7),corr.vec=NULL,corr.mat=corr.mat)

n.B=0
n.O=2
prop.list=list(cumsum(c(0.30, 0.40)), cumsum(c(0.4,0.2,0.3)))
corr.mat=matrix(c(1.0000000, -0.139923,-0.139923,1.0000000),2,2)
intmatOO=intermediate.corr.BO(n.B,n.O,prop.vec=NULL,prop.list,corr.vec=NULL, 
corr.mat)

#See IntermediateOO(plist, OOCorrMat) in R package OrdNor
#IntermediateOO(plist=list(cumsum(c(0.30,0.40)),cumsum(c(0.4,0.2,0.3))), 
OOCorrMat=corr.mat)

## End(Not run)

PoisBinOrd documentation built on March 22, 2021, 9:06 a.m.