[R] Looking for a textbook that is more concise than Applied Linear Statistical Models (2004 version)

[Gabor Grothendieck]

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