# Re: [R] Elegant way to express residual calculation in R?

From: Gabor Grothendieck <ggrothendieck_at_gmail.com>
Date: Tue 28 Feb 2006 - 15:43:04 EST

Here is one further idea:

Xm <- as.matrix(X)
Xm. <- scale(Xm, scale = FALSE)
Xm.. <- t(scale(t(tmp), scale = FALSE))
sum(Xm..^2)

On 2/27/06, Gabor Grothendieck <ggrothendieck@gmail.com> wrote:
> Try this:
>
> Xm <- as.matrix(X)
> X.lm <- lm(c(Xm) ~ factor(col(Xm)) + factor(row(Xm)))
> sum(resid(X.lm)^2)
>
> or if the idea was to do it without using lm try replacing
> your calculation of X.predicted with this:
>
> X.predicted <-
>
>
> On 2/27/06, John McHenry <john_d_mchenry@yahoo.com> wrote:
> > Hi All,
> >
> > I am illustrating a simple, two-way ANOVA using the following data and I'm
> > having difficulty in expressing the predicted values succinctly in R.
> >
> > Machine.1 Machine.2 Machine.3
> > 53 61 51
> > 47 55 51
> > 46 52 49
> > 50 58 54
> > 49 54 50"
> > rownames(X)<- paste("Operator.", 1:nrow(X), sep="")
> > print(X)
> >
> > # I'd like to know if there is a more elegant way to calculate the residuals
> > # than the following, which seems to be rather a kludge. If you care to read
> > # the code you'll see what I mean.
> >
> > X.predicted<- numeric(0)
> > for (j in 1:ncol(X))
> > {
> > X.predicted<- cbind(X.predicted, new.col)
> > }
> > print(X.predicted)
> > X.residual<- X - X.predicted
> > SS.E<- sum( X.residual^2 )
> >
> > It seems like there ought to be some way of doing that a little bit cleaner ...
> >
> > Thanks,
> >
> > Jack.
> >
> >
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