R: Computes an intermediate correlation matrix for continuous...
Int.Corr.NN
R Documentation
Computes an intermediate correlation matrix for continuous non-normal variables given the specified correlation
matrix
Description
This function computes the intermediate correlation matrix for continuous non-normal-continuous non-normal combinations as formulated in Demirtas et al.
(2012).
Vector of elements below the diagonal of correlation matrix ordered columnwise.
corr.mat
Specified correlation matrix.
coef.mat
Matrix of coefficients produced from fleishman.coef.
Value
A correlation matrix of size n.NN*n.NN.
References
Demirtas, H., Hedeker, D., and Mermelstein, R.J. (2012). Simulation of massive public health data by power polynomials.
Statistics in Medicine, 31(27), 3337-3346.
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BinNonNor)
Loading required package: BB
Loading required package: corpcor
Loading required package: mvtnorm
Loading required package: Matrix
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/BinNonNor/Int.Corr.NN.Rd_%03d_medium.png", width=480, height=480)
> ### Name: Int.Corr.NN
> ### Title: Computes an intermediate correlation matrix for continuous
> ### non-normal variables given the specified correlation matrix
> ### Aliases: Int.Corr.NN
>
> ### ** Examples
>
> n.NN=4
> corr.vec=NULL
> corr.mat=matrix(c(1.0,-0.3,-0.3,-0.3,-0.3,-0.3,
+ -0.3,1.0,-0.3,-0.3,-0.3,-0.3,
+ -0.3,-0.3,1.0,0.4,0.5,0.6,
+ -0.3,-0.3,0.4,1.0,0.7,0.8,
+ -0.3,-0.3,0.5,0.7,1.0,0.9,
+ -0.3,-0.3,0.6,0.8,0.9,1.0),6,byrow=TRUE)
>
> coef.mat=matrix(c(
+ -0.31375, 0.00000, 0.10045, -0.10448,
+ 0.82632, 1.08574, 1.10502, 0.98085,
+ 0.31375, 0.00000, -0.10045, 0.10448,
+ 0.02271, -0.02945, -0.04001, 0.00272),4,byrow=TRUE)
>
> intcor.mat=Int.Corr.NN(n.NN,corr.vec=NULL,corr.mat,coef.mat)
>
>
>
>
>
> dev.off()
null device
1
>