Markus Gesmann writes:
> Murray,
>
> How about creating an empty list and filling it during your loop:
>
> mod <- list()
> for (i in 1:6) {
> mod[[i]] <- lm(y ~ poly(x,i))
> print(summary(mod[[i]]))
> }
>
> All your models are than stored in one object and you can use lapply
to
> do something on them, like:
> lapply(mod, summary) or lapply(mod, coef)
I think it is important to see why this deceptively simple
solution does not achieve the result that Murray wanted.
Take any fitted model object, say mod[[4]]. For this object the
formula component of the call will be, literally, y ~ poly(x, i),
and not y ~ poly(x, 4), as would be required to use the object,
e.g. for prediction. In fact all objects have the same formula.
You could, of course, re-create i and some things would be OK,
but getting pretty messy.
You would still have a problem if you wanted to plot the fit with
termplot(), for example, as it would try to do a two-dimensional
plot of the component if both arguments to poly were variables.
>
> -----Original Message-----
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of
> [EMAIL PROTECTED]
> Sent: 01 August 2006 06:16
> To: [EMAIL PROTECTED]; r-help@stat.math.ethz.ch
> Subject: Re: [R] Fitting models in a loop
>
>
> Murray,
>
> Here is a general paradigm I tend to use for such problems. It
extends
> to fairly general model sequences, including different responses, &c
>
> First a couple of tiny, tricky but useful functions:
>
> subst <- function(Command, ...) do.call("substitute", list(Command,
> list(...)))
>
> abut <- function(...) ## jam things tightly together
> do.call("paste", c(lapply(list(...), as.character), sep = ""))
>
> Name <- function(...) as.name(do.call("abut", list(...)))
>
> Now the gist.
>
> fitCommand <- quote({
> MODELi <- lm(y ~ poly(x, degree = i), theData)
> print(summary(MODELi))
> })
> for(i in 1:6) {
> thisCommand <- subst(fitCommand, MODELi = Name("model_", i), i
=
> i)
> print(thisCommand) ## only as a check
> eval(thisCommand)
> }
>
> At this point you should have the results and
>
> objects(pat = "^model_")
>
> should list the fitted model objects, all of which can be updated,
> summarised, plotted, &c, because the information on their construction
> is all embedded in the call.
>
> Bill.
>
> -----Original Message-----
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of Murray
Jorgensen
> Sent: Tuesday, 1 August 2006 2:09 PM
> To: r-help@stat.math.ethz.ch
> Subject: [R] Fitting models in a loop
>
> If I want to display a few polynomial regression fits I can do
something
>
> like
>
> for (i in 1:6) {
> mod <- lm(y ~ poly(x,i))
> print(summary(mod))
> }
>
> Suppose that I don't want to over-write the fitted model objects,
> though. How do I create a list of blank fitted model objects for later
> use in a loop?
>
> Murray Jorgensen
> --
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