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This package transforms or simulates data with a target empirical covariance matrix supplied by the user. The details to obtain such data can be found in Christidis, Van Aelst and Zamar (2019) (https://arxiv.org/abs/1812.05678).
You can install the stable version on R CRAN.
install.packages("simTargetCov", dependencies = TRUE)You can install the development version from GitHub.
library(devtools)
devtools::install_github("AnthonyChristidis/simTargetCov")# Function to create target covariance matrix with kernel set to r
target_cor <- function(r, p){
Gamma <- diag(p)
for(i in 1:(p-1)){
for(j in (i+1):p){
Gamma[i,j] <- Gamma[j,i] <- r^(abs(i-j))
}
}
return(Gamma)
}
# Transformation of data to target empirical covariance
dat.target.cov <- simTargetCov(X = MASS::mvrnorm(30, mu = rep(0,6),
Sigma = target_cor(0.5,6)),
target = target_cor(0.5,6))
round(cov(dat.target.cov), 2)
# Simulation of data with target empirical covariance
sim.target.cov <- simTargetCov(n = 30, p = 6, target = target_cor(0.5,6))
round(cov(sim.target.cov), 2)This package is free and open source software, licensed under GPL (>= 2).
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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