R help - Sep 2009 - Looking for a textbook that is more concise than Applied Linear Statistical Models (2004 version)

Hi,

I know this is a little bit offtopic on this list. But I can't find a
more appropriate forum that I can ask. If there is a high quality
forum on statistics textbook discussion, please let me know.

I am reading Applied Linear Statistical Models. One drawback that I
feel about this book is that it discuss many examples, which is to
distracting. Numbers are give in those examples. Comments are buried
in the examples. If I skip the examples, I would miss some important
points. But if I don't skip the examples, it would take me too much
time to finish the book (this book is of 1000 pages)

However, I feel that the main points in the book can be concisely
written in the matrix form. Athough this book has include matrix
formulation, but it doesn't use it extensively. For example, the
examples are not written with the abstract matrix (I mean just using
symbols, such A, to represent the matrix)

I'm wondering if there is a well-written book that is more concise
than Applied Linear Statistical Models but roughly covers the same
topics?

Regards,
Peng

Check out Simon Wood's "Generalized Additive Models: An Introduction
with R".  Its actually a lot more than its title suggests with linear
model theory and related use of R in chapter 1 (and GLMs, GAMs, mixed
models and GAMMs in subsequent chapters plus an appendix on matrix
algebra).  Google for more info.

On Sat, Sep 26, 2009 at 9:45 AM, Peng Yu <pengyu.ut at gmail.com>
wrote:
> Hi,
>
> I know this is a little bit offtopic on this list. But I can't find a
> more appropriate forum that I can ask. If there is a high quality
> forum on statistics textbook discussion, please let me know.
>
> I am reading Applied Linear Statistical Models. One drawback that I
> feel about this book is that it discuss many examples, which is to
> distracting. Numbers are give in those examples. Comments are buried
> in the examples. If I skip the examples, I would miss some important
> points. But if I don't skip the examples, it would take me too much
> time to finish the book (this book is of 1000 pages)
>
> However, I feel that the main points in the book can be concisely
> written in the matrix form. Athough this book has include matrix
> formulation, but it doesn't use it extensively. For example, the
> examples are not written with the abstract matrix (I mean just using
> symbols, such A, to represent the matrix)
>
> I'm wondering if there is a well-written book that is more concise
> than Applied Linear Statistical Models but roughly covers the same
> topics?
>
> Regards,
> Peng