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#' @title Predict method for fitted matching models
#'
#' @description Calculate predicted values for matching models fitted with functions \code{stabit} and \code{stabit2}.
#'
#' @param object a fitted object of class \code{stabit}
#' @param newdata optionally, a data frame in which to look for variables with which to
#' predict. If omitted, the fitted linear predictors or the fitted response values are returned.
#' @param ... .
#'
#' @export
#'
#' @author Thilo Klein
#'
#' @keywords summary
#'
#' @references Klein, T. (2015a). \href{https://ideas.repec.org/p/cam/camdae/1521.html}{Does Anti-Diversification Pay? A One-Sided Matching Model of Microcredit}.
#' \emph{Cambridge Working Papers in Economics}, #1521.
#'
#' @examples
#'
#' ## load the results from Klein (2015) paper
#' data(klein15a)
#'
#' ## predict the latent outcome variable
#' predict(klein15a)
#'
predict.stabit2 <- function(object, newdata=NULL, ...){
if(object$method=="Klein-selection"){
stop("Prediction method not yet implemented for matching equations!")
}
if(is.null(newdata))
y <- fitted(object)
else{
if(!is.null(object$formula)){
## model has been fitted using formula interface
x <- model.matrix(object$formula, newdata)
}
else{
x <- newdata
}
y <- as.vector(x %*% object$coefs$alpha)
}
y
}
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