Nothing
#' @export
predict.cpalspath <- function(object, newx, s = NULL,
type = c("response", "scale"), ...) {
type <- match.arg(type)
b0 <- t(as.matrix(object$b0))
rownames(b0) <- "(Intercept)"
nbeta <- rbind2(b0, object$beta)
t0 <- t(as.matrix(object$t0))
rownames(t0) <- "(Intercept)"
ntheta <- rbind2(t0, object$theta)
if (!is.null(s)) {
lambda <- object$lambda
lamlist <- lambda.interp(lambda, s)
vnames <- dimnames(nbeta)[[1]]
dimnames(nbeta) <- list(NULL, NULL)
nbeta <- nbeta[,lamlist$left,drop=FALSE]%*%Diagonal(x=lamlist$frac) +
nbeta[,lamlist$right,drop=FALSE]%*%Diagonal(x=1-lamlist$frac)
dimnames(nbeta) <- list(vnames, paste(seq(along = s)))
vnames <- dimnames(ntheta)[[1]]
dimnames(ntheta) <- list(NULL, NULL)
ntheta <- ntheta[,lamlist$left,drop=FALSE]%*%Diagonal(x=lamlist$frac) +
ntheta[,lamlist$right,drop=FALSE]%*%Diagonal(x=1-lamlist$frac)
dimnames(ntheta) <- list(vnames, paste(seq(along = s)))
}
nfit <- switch(type,
response = as.matrix(as.matrix(cbind2(1, newx)) %*% nbeta),
scale = as.matrix(as.matrix(cbind2(1, newx)) %*% ntheta))
nfit
## nfit <- list(mean = as.matrix(as.matrix(cbind2(1, newx)) %*% nbeta),
## scale = as.matrix(as.matrix(cbind2(1, newx)) %*% nbeta))
## nfit
}
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