freshjx / r-program Goto Github PK

#计算模型中各个预测变量的权重，但只支持一元一维的线性回归模型
relweights <- function(fit,...){
R <- cor(fit$model)
nvar <- ncol(R)
rxx <- R[2:nvar,2:nvar]
rxy <- R[2:nvar,1]
svd <- eigen(rxx)#Computes eigenvalues and eigenvectors of numeric (double, integer, logical) or complex matrices.
evec <- svd$vectors
ev <- svd$values
delta <- diag(sqrt(ev))#Extract or replace the diagonal of a matrix, or construct a diagonal matrix.
lambda <- evec %% delta %% t(evec)
lambdasq <- lambda^2
beta <- solve(lambda) %% rxy
rsquare <- colSums(beta^2)
rawwgt <- lambdasq %% beta^2
import <- (rawwgt / rsquare) * 100
import <- as.data.frame(import)
row.names(import) <- names(fit$model[2:nvar])
names(import) <- 'Weights'
import <- import[order(import),1,drop=FALSE]
dotchart(import$Weights, labels = row.names(import),
xlab = '% of R-Square', pch = 19,
main = 'Relative Importance of Predictor Variabels',
sub = paste('Total R-Square=',round(rsquare,digits = 3)),
...)
return(import)
}