# transCCA: A package for estimation transelliptical CCA using the transformed Kendall’s scatter matrix estimator

The `transCCA` package estimates the transelliptical CCA directions and correlations, as well as their asymptotic variances using the transformed Kendall’s scatter matrix estimator.

## Installation

``````devtools::install_github("blangworthy/transCCA")
library(transCCA)
``````

##Examples

``````library(transCCA)
library(mvtnorm)

sigmax <- diag(8)
sigmay <- diag(8)
sigmaxy <- diag(c(0.9,0.5,0.4,1/3,rep(0,4)))

sigma <- rbind(cbind(sigmax,sigmaxy),cbind(sigmaxy,sigmay))####Scatter matrix for simulated data

z <- mvtnorm::rmvt(n=1000,sigma = sigma,df = 5)####Simulate from multivariate t distribution with 5 degrees of freedom

transccout <- transCCA(z[,1:8],z[,9:16])####Estimate the transelliptical canonical directions and correlations

dir1var <- transCorVar(z[,1:8],z[,9:16],1)####Asymptotic Variance estimates of transelliptical canonical directions and correlations

####Upper and lower bound for asymptotic confidence intervals for first direction

xdir1ub <- transccout\$xcoef[1,] + qnorm(0.975)*sqrt(diag(dir1var\$XCoefVar)/nrow(z))
xdir1lb <- transccout\$xcoef[1,] - qnorm(0.975)*sqrt(diag(dir1var\$XCoefVar)/nrow(z))

ydir1ub <- transccout\$ycoef[1,] + qnorm(0.975)*sqrt(diag(dir1var\$YCoefVar)/nrow(z))
ydir1lb <- transccout\$ycoef[1,] - qnorm(0.975)*sqrt(diag(dir1var\$YCoefVar)/nrow(z))

####Upper and lower bound for asymptotic confidence intervals for correlations
####Use bootstrap confidence intervals for transelliptical confidence correlations if sample size is small
corub <- min(transccout\$cancor + qnorm(0.975)*sqrt(dir1var\$corVar/nrow(z)),1)
corlb <- max(transccout\$cancor - qnorm(0.975)*sqrt(dir1var\$corVar/nrow(z)),0)
``````

For further examples see the following vignette

blangworthy/transCCA documentation built on Aug. 15, 2020, 7 a.m.