R/predict.R

In stpm: Stochastic Process Model for Analysis of Longitudinal and Time-to-Event Outcomes

#predict <- function(object, ...)
#UseMethod("predict")

## Predict function for spm
##@param object An object of class \code{spm}
##@param ... Other arguments passed to \code{predict}.
##@return A data frame consisting of predicted values of \code{Y}, 
##@return hazard \code{H}, \code{t}, \code{t.next}.
##@export
##@examples \dontrun{
##'library(stpm)
##'data <- simdata_discr(N=100, format="long")
##'res <- spm_discrete(data)
##'splitted <- split(data, data$id)
##'df <- data.frame()
##'lapply(1:100, 
##'       function(i) {
##'                      df<<-rbind(df,
##'                                 splitted[[i]][dim(splitted[[i]])[1],
##'                                                   c("id", "xi", "t1", "y1")])})
##'names(df) <- c("id", "xi", "t", "y")
##'predicted <- predict(object=res, x=df, dt=3)
##'head(predicted)
##'}
##'
#predict.spm <- function(object, ...) {
#    predict.default(object, ...)
#}
#
## Default prediction function for spm
##@param object An object of class \code{spm}
##@param x A data frame with current values of \code{Y} and \code{t}
##@param dt A time interval. Default: 8.
##@return A data frame consisting of predicted values of \code{Y}, 
##@return hazard \code{H}, \code{t}, \code{t.next}.
##@export
##
#predict.default <- function(object, x, dt=8) {
#    if(!(class(object) %in% c("spm", "spm.discrete", "spm.continuous"))) {
#        stop("Wrong class of object. It should be spm")
#    }
#    
#    
#    # Next value of Y:
#    pred.y <- c()
#    haz <- c()
#    for(i in 1:length(x$y)) {
#        pred.y <- c(pred.y, getNextY.cont(x$y[i], x$t[i], x$t[i]+dt, 
#                            object$cmodel$a, object$cmodel$f1, 
#                            object$cmodel$Q, object$cmodel$f, 
#                            object$cmodel$b, object$cmodel$theta))
#        haz <- c(haz, mu(x$y[i], object$cmodel$mu0, object$cmodel$b, 
#                object$cmodel$Q, object$cmodel$theta, time))
#    }
#    
#    
#    
#    res <- data.frame(cbind(pred.y = pred.y, 
#                            H=haz,
#                            t=x$t,
#                            t.next=x$t+dt))
#    
#    return(res)
#}