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boot.relimp.formula <- function(formula, data, weights, na.action, ..., subset=NULL){
if (missing(formula)) stop("formula missing")
if (missing(na.action))
na.action <- getOption("na.action")
m <- match.call(expand.dots = FALSE)
if (is.matrix(eval(m$data, parent.frame())))
m$data <- as.data.frame(data)
m[[1]] <- as.name("model.frame")
m$... <- NULL
mf <- eval(m, parent.frame())
terms <- attr(mf,"terms")
resp <- attr(terms,"response")
if (resp != 1 ) stop("incorrect formula")
if (max(attr(terms,"order")) > 2) stop ("formula contains terms of order higher than 2")
if (attr(terms,"intercept") != 1) stop ("model must contain intercept")
if (!is.null(attr(mf,"na.action"))) warning(naprint(attr(mf,"na.action")))
if (!is.null(dim(model.response(mf)))){
if (ncol(model.response(mf))>1) stop("too many response variables")
}
## selection of columns from model needed because of e.g. lm(y~x1+x2+x3-x2)
## selection of columns from model based on formula below
## works even in case of multi-column terms such as poly(x2,3)
#DATA <- as.matrix(mf[,c(resp,which(rowSums(attr(terms,"factors"))>0))])
#weights <- mf$"(weights)"
bt <- do.call("boot.relimp", list(lm(mf), ...))
bt
}
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