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...@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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
