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predict.mnp <- function(object, newdata = NULL, newdraw = NULL, n.draws = 1,
type = c("prob", "choice", "order"),
verbose = FALSE, ...){
if (NA %in% match(type, c("prob", "choice", "order")))
stop("Invalid input for `type'.")
if (n.draws < 1)
stop("Invalid input for `n.draws'.")
p <- object$n.alt
if (is.null(newdraw))
param <- object$param
else
param <- newdraw
n.cov <- ncol(coef(object))
coef <- param[,1:n.cov]
n.mcmc <- nrow(coef)
cov <- param[,(n.cov+1):ncol(param)]
## get X matrix ready
if (is.null(newdata))
x <- object$x
else {
call <- object$call
x <- xmatrix.mnp(as.formula(call$formula), data = newdata,
choiceX = call$choiceX,
cXnames = eval(call$cXnames),
base = object$base, n.dim = p-1,
lev = object$alt, MoP = is.matrix(object$y),
verbose = FALSE, extra = FALSE)
if (nrow(x) > 1)
x <- as.matrix(x[apply(is.na(x), 1, sum)==0,])
else if (sum(is.na(x))>0)
stop("Invalid input for `newdata'.")
}
n.obs <- nrow(x)
if (verbose) {
if (n.obs == 1)
cat("There is one observation to predict. Please wait...\n")
else
cat("There are", n.obs, "observations to predict. Please wait...\n")
}
alt <- object$alt
if (object$base != alt[1])
alt <- c(object$base, alt[1:(length(alt)-1)])
res <- .C("predict", as.double(x), as.integer(n.obs),
as.double(coef), as.double(cov), as.integer(p-1),
as.integer(n.cov), as.integer(n.mcmc),
as.integer(n.draws), as.integer(verbose),
prob = if (n.draws > 1) double(n.obs*n.mcmc*p)
else double(n.obs*p),
choice = double(n.obs*n.mcmc),
order = double(n.obs*n.mcmc*p),
PACKAGE = "MNP")
ans <- list()
if ("choice" %in% type)
ans$y <- matrix(res$choice, ncol=n.mcmc, nrow = n.obs,
byrow = TRUE, dimnames = list(rownames(x), 1:n.mcmc))
else
ans$y <- NULL
if ("order" %in% type)
ans$o <- aperm(array(res$order, dim=c(p, n.mcmc, n.obs),
dimnames = list(alt, 1:n.mcmc,
rownames(x))), c(3,1,2))
else
ans$o <- NULL
if ("prob" %in% type)
if (n.draws > 1)
ans$p <- aperm(array(res$prob, dim = c(p, n.mcmc, n.obs),
dimnames = list(alt, 1:n.mcmc,
rownames(x))), c(3,1,2))
else
ans$p <- matrix(res$prob, nrow = n.obs, ncol = p, byrow = TRUE,
dimnames = list(rownames(x), alt))
else
ans$p <- NULL
ans$x <- x
class(ans) <- "predict.mnp"
return(ans)
}
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