Nothing
predict.panelAR <- function(object,newdata=NULL,se.fit = FALSE,
conf.interval = FALSE, conf.level = 0.95, na.action=na.pass,...){
beta <- object$coefficients
tt <- terms(object)
terms <- delete.response(tt)
df <- object$df
if (missing(newdata) || is.null(newdata)) {
yhat <- object$fitted.values
X <- model.matrix(terms,out$model)
} else{
mf <- model.frame(terms, newdata, na.action = na.action)
# pull class descriptions of variables and see if they match the model frame
.checkMFClasses(attr(terms, "dataClasses"), mf)
X <- model.matrix(terms, mf)
yhat <- X %*% beta
}
if(se.fit || conf.interval){
fit.out <- data.frame(fit=yhat)
d <- diag(X%*%object$vcov%*%t(X))
d[d<0] <- NA
se <- sqrt(d)
if(se.fit){
fit.out$se <- se
}
if(conf.interval){
fit.out$lb <- yhat + se*qt((1-conf.level)/2,df=df)
fit.out$ub <- yhat + se*qt(1-(1-conf.level)/2,df=df)
}
} else{
fit.out <- yhat
}
out <- list(fit=fit.out,df=df)
out
}
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