convertbeta {sparsenetgls} | R Documentation |
The covertbeta function is designed to convert the regression coefficients derived from the standardized data.
convertbeta(X, Y, q, beta0)
X |
It is a dataset of explanatory variables. |
Y |
It is the multivariate response variables. |
q |
It is an integer representing the number of explanatory variables. |
beta0 |
The vector contains the regression coefficients from sparsenetgls. |
Return the list of converted regression coefficients of the explanatory variables 'betaconv' and intercept value 'betaconv_int'.
X <- mvrnorm(n=20,mu=rep(0,5),Sigma=Diagonal(5,rep(1,5))) Y <- mvrnorm(n=20,mu=rep(0.5,10),Sigma=Diagonal(10,rep(1,10))) fitmodel <- sparsenetgls(responsedata=Y,predictdata=X,nlambda=5,ndist=2, method='elastic') convertbeta(X=X,Y=Y,q=5+1,beta0=fitmodel$beta[,1])