1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42
|
predict.ecoNPX <- function(object, newdraw = NULL, subset = NULL,
obs = NULL, cond = FALSE, verbose = FALSE, ...){
if (is.null(newdraw) && is.null(object$mu))
stop("Posterior draws of mu and Sigma must be supplied")
else if (!is.null(newdraw)){
if (is.null(newdraw$mu) && is.null(newdraw$Sigma))
stop("Posterior draws of both mu and Sigma must be supplied.")
object <- newdraw
}
n.draws <- dim(object$mu)[1]
n <- dim(object$mu)[3]
mu <- aperm(coef(object, subset = subset, obs = obs), c(2,3,1))
if (is.null(subset))
subset <- 1:n.draws
if (is.null(obs))
obs <- 1:n
Sigma <- aperm(object$Sigma[subset,,obs], c(2,3,1))
if (cond) { # conditional prediction
X <- object$X
res <- .C("preDPX", as.double(mu), as.double(Sigma), as.double(X),
as.integer(n), as.integer(n.draws), as.integer(2),
as.integer(verbose), pdStore = double(n.draws*2*n),
PACKAGE="eco")$pdStore
res <- matrix(res, ncol=2, nrow=n.draws*n, byrow=TRUE)
colnames(res) <- c("W1", "W2")
}
else { # unconditional prediction
res <- .C("preDP", as.double(mu), as.double(Sigma), as.integer(n),
as.integer(n.draws), as.integer(3), as.integer(verbose),
pdStore = double(n.draws*3*n), PACKAGE="eco")$pdStore
res <- matrix(res, ncol=3, nrow=n.draws*n, byrow=TRUE)
colnames(res) <- c("W1", "W2", "X")
}
class(res) <- c("predict.eco", "matrix")
return(res)
}
|