Nothing
"grouped" <-
function(formula, link = c("identity", "log", "logit"), distribution = c("normal", "t", "logistic"),
data, subset, na.action, str.values, df = NULL, iter = 3, ...){
cl <- match.call()
mf <- match.call(expand.dots=FALSE)
m <- match(c("formula", "data", "subset", "na.action"), names(mf), 0)
mf <- mf[c(1, m)]
mf$drop.unused.levels <- TRUE
mf[[1]] <- as.name("model.frame")
mf <- eval(mf, parent.frame())
mt <- attr(mf, "terms")
y <- model.response(mf, "numeric")
if(is.empty.model(mt)){
fit <- list(coefficients = NULL, logLik = NULL, hessian = NULL, k = NULL, n = n)
} else{
distr <- match.arg(distribution)
if(is.null(df) && distr == "t")
stop("You must specify the degrees of freedom for the Student's-t distribution.\n")
if(!is.null(df) && distr != "t")
warning("you specified the `df' argument and you don't use the Student's-t as reference distribution.\n")
link <- match.arg(link)
X <- model.matrix(mt, mf)
fit <- grouped.fit(y, X, link, distr, df, starts = str.values, iter)
}
fit$call <- cl
class(fit) <- "grouped"
fit
}
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