Nothing
##########
# Internal method that prepare non-linear effects plots (only single index at the moment)
#
.prepareNested<- function(o, n, xlim, ...){
gObj <- o$gObj
sm <- gObj$smooth[[ o$ism ]]
# Get single index vector
si <- sm$xt$si
raw <- sort( si$X %*% si$alpha )
dsi <- length( si$alpha )
# Get regression coeff of outer smooth
prange <- (sm$first.para:sm$last.para)[-(1:dsi)]
beta <- coef( gObj )[ prange ]
# Generate x sequence for prediction
if (is.null(xlim)){
xlim <- range(raw)
}
xx <- seq(xlim[1], xlim[2], length = n)
# Compute outer model matrix
X <- sm$xt$splineDes(x = xx, deriv = 0)$X0
fit <- X %*% beta
se <- sqrt(pmax(0, rowSums((X %*% gObj$Vp[prange, prange, drop = FALSE]) * X)))
edf <- sum(gObj$edf[prange])
ylabel <- .subEDF(paste0("s(proj(", sm$term, "))"), edf)
xlabel <- paste0("proj(", sm$term, ")")
out <- list("fit" = fit, "x" = xx, "se" = se, "raw" = raw, "xlim" = xlim,
xlab = xlabel, ylab = ylabel, main = NULL)
return(out)
}
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