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# Make predictions from a given "plrs" model
# Author: Gwenael G.R. Leday
predict.plrs <- function(object, newcghseg, ...){
if(class(object)!="plrs") stop("An object of class \"plrs\" is required")
if(!is.vector(newcghseg)) stop("Object \"newcghseg\" has to be a vector")
X <- .Bmat(newcghseg, knots = object@data$knots,
continuous = object@call.arg$continuous,
general.intercept = T)
if(object@selected) X <- X[,colnames(X)%in%names(coef(object))]
fit.val <- as.vector(crossprod(t(X), coef(object)))
return(fit.val)
}
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