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#' Sensitivity indices based on simple and standard regression analyses
#' @param X a design dataframe
#' @param Y a dataframe of responses
#' @param model the regression model
#' @value a list of regression results
#' @note This function is essentially a (possibly repeated) call to the "src" function of the R sensitivity package
regressionSI <- function(X, Y, rank=FALSE, nboot=100, conf=0.95, ...){
## PRELIMINARIES
nf <- ncol(Y)
Ynames <- names(Y)
results <- vector(mode="list", length=nf)
## MAIN CALCULATIONS
for(i in seq(nf)){
resultsA <- src(X, Y[,i], rank=rank, nboot=nboot, conf=conf)
if(!rank)
results[[i]] <- resultsA[c("SRC")]
else
results[[i]] <- resultsA[c("SRRC")]
}
## Output
output <- list(main=results, information=list(Ynames=Ynames,rank=rank,nboot=nboot,conf=conf))
return(output)
}
print.regressionSI <- function(x, ...){
## PRELIMINARIES
results <- x$main
Ynames <- x$information$Ynames
rank <- x$information$rank
nf <- length(results)
## MAIN CALCULATIONS
cat("\nStandardized Regression Coefficients (SRC)\n")
cat(" calculated by the src function of the sensitivity library\n")
cat(" with parameters rank = ", x$information$rank,
", nboot = ", x$information$nboot,
", conf = ", x$information$conf,
"\n\n")
for(i in seq(nf)){
cat("Response variable: ", Ynames[i], "\n")
print(results[[i]])
}
invisible()
}
plot.regressionSI <- function(x,y, ...){
## PRELIMINARIES
results <- x$main
Ynames <- x$information$Ynames
rank <- x$information$rank
nf <- length(results)
## MAIN CALCULATIONS
nb.col <- ceiling(sqrt(nf))
nb.row <- ceiling(nf/nb.col)
keep.mfrow <- par(mfrow=c(nb.row,nb.col))
for(i in seq(nf)){
src.obj.i <- results[[i]]
class(src.obj.i) <- "src"
plot(src.obj.i, ...)
title(xlab=Ynames[i])
abline(h=0)
}
par(keep.mfrow)
invisible()
}
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