Thanks for the reply. Unfortunately, "do.call" strips off the subset identifiers, which I want to use for further modeling:
> do.call("rbind", byFits)
(Intercept) x
[1,] 0.3333333 -1.517960e-016
[2,] 0.6666667 3.282015e-016The following does what I want using a "for" loop:
> by.df <- data.frame(A=rep(c("A1", "A2"), each=3),
+ B=rep(c("B1", "B2"), each=3), x=1:6, y=rep(0:1, length=6))
> by.lvls <- paste(as.character(by.df$A), as.character(by.df$B), sep=":")
> A.B <- unique(by.lvls)
> Fits <- data.frame(A.B = A.B, .Intercept.=rep(NA, length(A.B)),
+ x=rep(NA, length(A.B)))
> Fits$A <- substring(A.B, 1, regexpr(":", A.B)-1)
> Fits$B <- substring(A.B, regexpr(":", A.B)+1)
> for(i in 1:length(A.B))
+ Fits[i, 2:3] <- coef(lm(y~x, by.df[by.lvls==A.B[i],]))
> Fits
A.B X.Intercept. x A B
1 A1:B1 0.3333333 -1.517960e-16 A1 B1
2 A2:B2 0.6666667 3.282015e-16 A2 B2
>I wondered if there was something easier.
Thanks again for your reply. Spencer Graves
Thomas Lumley wrote:
On Thu, 5 Jun 2003, Spencer Graves wrote:
Dear R-Help:
I want to (a) subset a data.frame by several columns, (b) fit a model to each subset, and (c) store a vector of results from the fit in the columns of a data.frame. In the past, I've used "for" loops do do this. Is there a way to use "by"?
Consider the following example:
> byFits <- by(by.df, list(A=by.df$A, B=by.df$B), + function(data.)coef(lm(y~x, data.))) > byFits A: A1 B: B1 (Intercept) x 3.333333e-01 -1.517960e-16 ------------------------------------------------------------ A: A2 B: B1 NULL ------------------------------------------------------------ A: A1 B: B2 NULL ------------------------------------------------------------ A: A2 B: B2 (Intercept) x 6.666667e-01 3.282015e-16 > > ############################# Desired output:
data.frame(A=c("A1","A2"), B=c("B1", "B2"), .Intercept.=c(1/3, 2/3), x=c(-1.5e-16, 3.3e-16))
What's the simplest way to do this?
do.call("rbind", byFits)
-thomas
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