I imitated predict.glm, my thing worked, now I need to revise. It would
help me very much if someone would explain predict.glm line 28, which says
object$na.action <- NULL # kill this for predict.lm calls
I want to know
1) why does it set the object$na.action to NULL
2) what does the comment after mean?
Maybe I need a pass by value lesson too, because I can't see how changing
that in object would have any effect on calculations done elsewhere.
pj
Here's the context from predict.glm, to save you trouble of looking it up:
predict.glm <-
function(object, newdata = NULL, type = c("link", "response", "terms"),
se.fit = FALSE, dispersion = NULL, terms = NULL,
na.action = na.pass, ...)
{
## 1998/06/23 KH: predict.lm() now merged with the version in lm.R
type <- match.arg(type)
na.act <- object$na.action
object$na.action <- NULL # kill this for predict.lm calls
if (!se.fit) {
## No standard errors
if(missing(newdata)) {
pred <- switch(type,
link = object$linear.predictors,
response = object$fitted.values,
terms = predict.lm(object, se.fit = se.fit,
scale = 1, type = "terms", terms = terms)
)
if(!is.null(na.act)) pred <- napredict(na.act, pred)
} else {
pred <- predict.lm(object, newdata, se.fit, scale = 1,
type = ifelse(type == "link", "response",
type),
terms = terms, na.action = na.action)
switch(type,
response = {pred <- family(object)$linkinv(pred)},
link = , terms = )
}
} else {
## summary.survreg has no ... argument.
if(inherits(object, "survreg")) dispersion <- 1.
if(is.null(dispersion) || dispersion == 0)
dispersion <- summary(object, dispersion=dispersion)$dispersion
residual.scale <- as.vector(sqrt(dispersion))
pred <- predict.lm(object, newdata, se.fit, scale = residual.scale,
type = ifelse(type == "link", "response", type),
terms = terms, na.action = na.action)
fit <- pred$fit
se.fit <- pred$se.fit
switch(type,
response = {
se.fit <- se.fit * abs(family(object)$mu.eta(fit))
fit <- family(object)$linkinv(fit)
},
link = , terms = )
if( missing(newdata) && !is.null(na.act) ) {
fit <- napredict(na.act, fit)
se.fit <- napredict(na.act, se.fit)
}
pred <- list(fit = fit, se.fit = se.fit, residual.scale =
residual.scale)
}
pred
}
--
Paul E. Johnson
Professor, Political Science Assoc. Director
1541 Lilac Lane, Room 504 Center for Research Methods
University of Kansas University of Kansas
http://pj.freefaculty.org http://quant.ku.edu
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