[R] Customized R Regression Output?

[Rui Barradas]

Hello,

Actually, Bert is right, c() seems better. Chris wants a table with one 
row per dataset and columns like he wrote in a previous post.
Something like this could do it.

#------------------------ this was already posted
x1 <- 1:100
x2 <- log(x1^2)
y1 <- x1 + x2 + rnorm(100)
y2 <- x1*runif(100, 0.5, 1.0) + x2 + rnorm(100)

predictors <- c("x1", "x2")
responses <- c("y1", "y2")

fmla <- paste(responses, paste(predictors, collapse="+"), sep="~")

model <- vector("list", length(fmla))
for(i in seq_along(fmla))
     model[[i]] <- lm(as.formula(fmla[i]))

#------------------------ make the table
nr <- length(model)
nc <- nrow(coef(summary(model[[1]])))
tbl <- matrix(nrow=nr, ncol=2*nc + 1, dimnames=list(seq_len(nr), 
seq_len(2*nc + 1)))
for(i in seq_along(model)){
     smry <- summary(model[[i]])
     tbl[i, ] <- c(t(coef(smry)[ , c(1, 4)]), smry$r.squared)  # uses c()
}
colnames(tbl)[2*1:nc - 1] <- rownames(coef(smry))
colnames(tbl)[2*1:nc] <- paste("p.value", 0:(nc - 1), sep=".") # see below
colnames(tbl)[2*nc + 1] <- "R2"
tbl


If the only purpose is a printout, I would skip the 'paste', it would be 
obvious which regressor the p.value corresponds to. But if the matrix is 
to be used for other ends, duplicate names are a bad idea.

Rui Barradas


Em 27-05-2012 19:55, Özgür Asar escreveu:
> Dear Bert Gunter,
>
> Doesn't the summary(lm1)$coef have a matrix form? Then, while working with
> columns of a matrix, can't one use c/rbind functions?
>
> But list seem to better for what Chris asked. Nonetheless, c does not.
>
> Best
> Ozgur
>
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>
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> Middle East Technical University
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