A suggestion for predict function(s)
From: Ross Darnell Liaw, Andy wrote:
I must respectfully disagree. Why carry extra copies of
data arround? This
is probably OK for small to medium sized data, but
definitely not for large
data. Besides, in your example, it may do different things
depending on whether
newdata is supplied: model.matrix is not necessarily the
same as the
original data frame. You need a bit more work to get the
right model.matrix
that correspond to the newdata. It's not clear to me
whether you want to
return model matrix or model frame, but in either case it's
not sufficient
to just use `newdata'. Andy
From: Ross Darnell
Maybe a useful addition to the predict functions would be to
return the
values of the predictor variables. It just (unless there are
problems)
requires an extra line. I have inserted an example below.
"predict.glm" <-
function (object, newdata = NULL, type = c("link", "response",
[snip]
Ross Darnell -- School of Health and Rehabilitation Sciences University of Queensland, Brisbane QLD 4072 AUSTRALIA Email: <r.darnell at uq.edu.au> Phone: +61 7 3365 6087 Fax: +61 7 3365 4754 Room:822, Therapies Bldg. http://www.shrs.uq.edu.au/shrs/school_staff/ross_darnell.html
A good point but what is the value of storing a large set of predicted values when the values of the explanatory variables are lost (predicted values of what?). I thought the purpose of objects was that they were self explanatory (pardon the pun). Maybe we could make it optional.
If what you are looking for is a way to track the observations, I'd suggest simply adding rownames of newdata as names of the predicted values. Storing names is much cheaper than the entire data frame of predictors. (And in R, data frames _must_ have unique row names.) Cheers, Andy
Ross Darnell -- Email: <r.darnell at uq.edu.au>