Nothing
residuals.mixreg <- function(object,std=FALSE,...) {
fmla <- object$formula
noPred <- length(all.vars(fmla)) == 1
intcpt <- as.logical(attr(terms(fmla),"intercept"))
xm <- model.matrix(fmla,data=object$data)
if(noPred) {
pnms <- "index"
x <- 1:nrow(xm)
} else {
pnms <- if(intcpt) colnames(xm)[-1] else colnames(xm)
x <- if(intcpt) drop(xm[,-1]) else xm
}
nmy <- all.vars(fmla)[1]
y <- object$data[[nmy]]
# Note that "vnms" consists of "reasonable" names for the response
# and all of the individual (vector) predictors, even if some the
# terms on the right hand side of "fmla" are matrices.
vnms <- c(nmy,pnms)
theta <- object$theta
K <- length(theta)
resid <- vector("list",K)
fvals <- vector("list",K)
gamma <- gfun(xm,y,theta)$gamma
for(k in 1:K) {
div <- if(std) {
sqrt(hatfun(xm,gamma[,k])*theta[[k]]$sigsq)
} else {
1
}
fitz <- drop(xm%*%theta[[k]]$beta)
fvals[[k]] <- fitz
resid[[k]] <- (y-fitz)/div
}
rslt <- list(resid=matrix(unlist(resid),ncol=K),
fvals=matrix(unlist(fvals),ncol=K),
gamma=gamma,x=x,y=y,vnms=vnms,noPred=noPred)
class(rslt) <- "mixresid"
rslt
}
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