Nothing
avplot_fun.glm <- function(model, variable, type, label.id, n.label.id, xlab, ylab, main,
pos, pch, cex, lcol, lwd, lty, ...) {
n.obs <- nobs(model)
index <- seq_len(n.obs)
frm <- formula(model)
y.name <- as.character(frm[2])
if(missing(label.id)) label.id <- index
if(missing(n.label.id)) n.label.id <- 2
if(missing(xlab)) xlab <- paste(variable, '- residuals')
if(missing(ylab)) ylab <- paste(y.name, '- residuals')
if(missing(main)) main <- paste('Added variable plot -', variable)
if(missing(pos)) pos <- 2
if(missing(pch)) pch <- 16
if(missing(cex)) cex <- .9
if(missing(lcol)) lcol <- 2
if(missing(lwd)) lwd <- 1.5
if(missing(lty)) lty <- 2
mm <- model.matrix(model)
var.names <- colnames(mm)
var.index <- which(var.names == variable)
var <- mm[ , var.index]
mm.red <- mm[, -var.index, drop = F]
if(!missing(variable)) if(!(variable %in% var.names)) stop('variable not found')
y <- model$y
prior.w <- model$prior.weights
mod.red <- glm.fit(x = mm.red, y = y, weights = prior.w, family = family(model))
class(mod.red) <- 'glm'
wres <- residuals(mod.red, type = 'working')
w <- if(type == 'Wang') sqrt(mod.red$weights)
else sqrt(model$weights)
res.y <- w * wres
res.x <- lm.wfit(x = mm.red, y = var, w = w * prior.w)$residuals
res.lm <- lm(res.y ~ res.x, weights = w * prior.w)
res.cd <- cooks.distance(res.lm)
points.lab <- getMaxIndex(res.cd, label.id, k = n.label.id)
plot(x = res.x, y = res.y, xlab = xlab, ylab = ylab,
main = main, pch = pch, cex = cex, ...)
abline(res.lm, col = lcol, lwd = lwd, lty = lty)
text(x = res.x, y = res.y, label = points.lab, pos = pos)
}
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