[EMAIL PROTECTED] (Cornilia) wrote:

> I have a training data set, and I want to obtain the LOOCV error rate
> for a linear regression model. How can I implement this in R or
> S-Plus? I can use for loop and fit linear models n times, with one row
> out each time. My main problem is that I don't know how to leave one
> row out of my data set in lm function within the for loop.
[...]

In the S language, a negative index means "all but this index". 
Let's say X is a matrix. Then X[-i,] is all rows except the i'th row.
(The missing column index means "all columns".)

But do you really need to do that? If I recall correctly there is a
formula for the leave-one-out cross-validation error. Or maybe I'm
thinking of the so-called generalized cross-validation error. Sorry,
I'm too lazy to go look it up right now.

You might look at the contributed packages at: http://www.r-project.org
I wouldn't be surprised if someone has already put something together
for cross-validation.

BTW it is a good idea to spell out abbreviations; you want as many
people as possible to understand the question. YMMV.

For what it's worth,
Robert Dodier
.
.
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