#' @title Summarizes a sfmfep fitted model
#' @description summary.sfmfep is the sfmfep specific method for
#' the generic function summary which summarize objects
#' returned by modelling functions.
#' @param ... Additional arguments to the function
#' @param object is a data frame of the inefficencys per panel.
#' @param digits defines the amount of digits for the values of the summary
#' @export
summary.sfmfep <- function(object, digits = max(3L, getOption("digits") - 3L), ...){
if(object$estimate){
head2 <- c("alpha", "inefficiency")
mat2 <- matrix(NA, length(object$alpha), length(head2),
dimnames = list(rownames(object$alpha), head2))
mat2[, 1] <- object$alpha
mat2[, 2] <- object$Ineff
if(!is.null(object$standerror)){
head1 <- c("Coefficients", "Std.Error")
mat1 <- matrix(NA, length(object$contrasts), length(head1),
dimnames = list(object$contrasts, head1))
mat1[, 1] <- object$coefficients
mat1[, 2] <- object$standerror
if(!is.null(object$conf)){
mat1 <- cbind(mat1, object$conf)
}
} else {
head1 <- c("Coefficients")
mat1 <- matrix(NA, length(object$contrasts), length(head1),
dimnames = list(object$contrasts, head1))
mat1[, 1] <- object$coefficients
if(!is.null(object$conf)){
mat1 <- cbind(mat1, object$conf)
}
}
cat("Call:\n",
paste(deparse(object$call), sep = "\n", collapse = "\n"), "\n\n", sep = "")
if(object$bootstrap == T){
cat("method:", deparse(object$method), "\nEstimates are based on ",
object$B , "bootstrap samples\n\n")
} else {
cat("method:", deparse(object$method), "\n\n")
}
if(!is.null(object$conf)){
cat("Coefficients:\t\t\t\t\tconfInterval\n")
} else {
cat("Coefficients:\n")
}
printCoefmat (mat1)
cat("\nlog.Likelihood:", deparse(round(object$objective, digits)),
"; AIC:", deparse(round(object$aic, digits)),
"; BIC:", deparse(round(object$bic, digits)), "\n\n")
printCoefmat (mat2)
} else {
cat("Likelihood:", deparse(round(object$objective, digits)))
}
}
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