In livioivil/acca: A Canonical Correlation Analysis with Inferential Guaranties

knitr::opts_chunk$set(echo = TRUE)

acca: a canonical correlation analysis

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SetUp

To install this package (in R):

#if devtools is not installed yet: 
# install.packages("devtools") 
library(devtools)
install_github("livioivil/acca")

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L=matrix(rnorm(100),100,1)
X=matrix(rnorm(500),100,5)
Y=matrix(rnorm(700),100,7)
Z=matrix(rnorm(200),100,2)
X[,1]=X[,1]+2*L
Y[,1]=Y[,1]+2*L


library(acca)
mod=cc(X,Y,Z)
mod

ggbiplot2(mod)


L=matrix(rnorm(10),10,1)
X=matrix(rnorm(20),10,2)
Y=matrix(rnorm(30),10,3)
X[,1]=X[,1]+2*L
Y[,1]=Y[,1]+2*L

X=scale(X)
Y=scale(Y)

S11=cov(X)
ei=eigen(S11)
S11sqrtinv=ei$vectors%*%diag(ei$values^-.5)%*%t(ei$vectors)
S22=cov(Y)
ei=eigen(S22)
S22sqrtinv=ei$vectors%*%diag(ei$values^-.5)%*%t(ei$vectors)
S12=cov(X,Y)

sv=svd(S11sqrtinv%*%S12%*%S22sqrtinv)

sv

mod=acca::cc(X,Y)
mod

modcc=CCA::cc(X,Y)
modcc$cor

modcc$xcoef
mod$xcoef
sv$u
plot(mod$scores$xscores[,1],modcc$scores$xscores[,1])

mod0=cancor(X, Y, xcenter = TRUE, ycenter = TRUE)
mod0$xcoef
mod$xcoef
modcc$xcoef

mod0$ycoef
modcc$ycoef
mod$ycoef/mod0$ycoef[,-3]
mod$ycoef/modcc$ycoef

Testing null correlation of the canonical compoments

mod=cc_inference(mod,B = 1000,numb_cc = 3)
summary(mod)

livioivil/acca documentation built on Jan. 28, 2022, 7:37 p.m.