Modeling

This book is absolutely remarkable.

It presents the material traditionally taught in the second-year statistics (but actually goes well beyond, e.g. stochastic processes) and will be of interest to all people interested to (re-)learn statistics well, either undergraduates, or advanced students of any level. Professors should also read it maybe use it in class. Students will thank them.

The author took more than 14 years to polish it, and I would bet that scholars of pedagogy will put this book as an example of the highest possible level of their discipline. I would also bet that this book will have a long and brilliant career in statistical education. On gets the feeling that the author gave the same care and energy to the elaboration of this book as people commonly give to research.

The author is also a man with a mission. In his preface, one can read with pleasure and disbelief a passionate attack on the dumbing-down of undergraduate education in Europe and America. Having taught undergrads in commerce with the "predigested pap" he is talking about, I can really relate to the frustration of the author. There is no dilution of material or dumbing down here: all the ugly details are given, which makes that book not only a pedagogical tool but also a great reference.

There is no book on the market that is so polished in both presentation and discussion, that exposes intermediate stats at such an intelligent, comprehensive level, and finally that uses the historical development to project such clarity on the actual state of the science. I would say the closest competitor to this book is the great volume "Intermediate Statistics" by Dale Poirier, which has more econometrics and which might be a bit more comprehensive on the bayesian side, but the main focus of this one is on UNDERSTANDING and SYNTHESIZING. By the way, the focus of this book is statistics, not econometrics, despite the fact that the author has written extensively in econometrics.

I wish I would be an undergrad again and re-learn statistics with this book. Nevertheless, readers of all levels will learn something from it.

Ah, and the price is right. Value for your money!

Like many, I used the 1986 big green Spanos book to learn econometrics. Simply put, this latest follows the course charted by the first book -- it first covers probability theory, and then uses this to motivate the modelling portion of the book. Unlike the 1986 book, which was terse in places, this monograph is much more comprehensive. It isn't so much that new subjects are covered (though some are), but the current treatment far surpasses the 1986 book. More graphs, to aid geometric intution, are included. More text discusses the implications of the mathematics. More useful, in short, for a graduate student trying to learn econometrics. The only book I think is in this class is DeGroot, and that book suffers from little attention paid to econometrics (though it does do the probability material quite well).

Highly, highly recommended. And one other bonus: Spanos discusses in the introduction why he refuses to water things down, and even has a quote from the mathemetician Binmore.

I own a number of econometric and statistics texts, but this is easily the most comprehensive and probably the most important stats book that I own. Not only does it cover just about every stat concept one would need for doing applied research, but it teaches the reader how to think logically and clearly about econometrics problems. It teaches the reader how to properly integrate economic theory and statistical information for conducting good research. If you want to learn applied econometrics the proper way, read this book.

This book is simply great.... One can not believe that a highly complex and challenging arena of datawarehousing can be explained and understood in such a simple manner. It is amazing to see Amitesh unleashing the power of his thoughts and experiences to unveil this subject which has been alluding even big businesses for quite some time. This book empowers managers to ignite their imagination. The book helps the business to utilise tremendous potential which lay hidden in its own data base. I congratulate Amitesh Sinha for his excellent work.

The book is very useful book and is suited for all catagories of users - novices to experts. It not only covers the fundamentals & basic concepts of data warehousing but also deals with the subject in adequate depth. It helps one understand manipulation of data which provides your company with the information it needs in a timely manner and in an appropriate desired form. The author has done full justice to the profound subject that Data Warehousing is. It is a must read for project managers & developers who wish to start a new Data Warehouse application or re-inforce an existing one.

Have read this book and found it to be very interesting. It covers everything that is required to know Data Warehousing and its principles.
Any project manager or developer in the Data Warehousing field would find this book very useful to start a new data warehouse or reinforce an existing data warehouse.

Clear examples, clean derivations, and easy to understand style has Monson Hayes' his signature written all over it. I have his schaum's outline on DSP, and its just as good. I haven't finish perusing this book; i am currently on signal modeling (ch.3, i think) where pade, shank and other methods are derived, and i've already found plenty of application to work on.

homework problems include both mathematical and computer (matlab) exercises that help cement understanding the material at the end of each chapter.

applicable, yet theoretically appealing, this book is best for those who has had an introductory DSP course, although it is very much self-contained - the author starts with a comprehensive review of linear algebra and random processes - it will serve the serious student with an interest on statistical description of signals and system very well.

The book is beautiful, really neat. It contains all the essential topics that you will expect in a Spectral Analysis book. I stumbled across it in library and was impressed with the treatment that the author gave this subject. I now have a copy of my own. The topics range from basic to advanced including a few topics on adaptive filter theory.

Each treatment is almost immediately followed by an example, simple but powerful way to introduce you to this topic. I found this one feauture made the topics covered really enjoyable. Linear algebra review captures the essence of the style of this book. It is a welcome addition to this area in DSP. The one by Stocia is too mathematical to be called an introductory book. This one is way much above Stocia's mathematical nightmare.

I used this book to learn nearly all the topics covered in a hurry, in order to take the prelim exam at Berkeley. While it was a humbling experience, it made me truly learn to appreciate and love this book, and its great presentation and organization.

It starts off with a very good introduction to linear algebra and probability theory for engineers, which should give you a taste of the effective way that this book is laid out. The format is excellent, and the important points clearly highlighted. This is a real joy to read!

The magic doesn't wear off into the later chapters, which include topics in signal modeling, least-squares methods, MMSE estimation, Levinson algorithm, spectral estimation, and adaptive filters.

I find this book to be a great source for both learning and reference, and as a bonus it includes Matlab codes for all the algorithms mentioned here.

One complain is that there are certain topics that could be covered more effectively. For example, the relationship between the different signal models and filtering is not mentioned, and this could help understand the motivation of the different signal models in the first place.

Anyway, once you get past Oppenheim/Schafer, Proakis/Manolakis and Lyons' material this can be a great way to start your journey into the more advanced topics in signal processing.

This outstanding book was one of the mainstays for my Ph.D. dissertation. It explain factor analysis and SEM techniques in a clear and effective way, with an hands-on approach that guides the reader during all the data analysis and result interpretation phases.

I really needed this for my dissertation. As a computer scientist who is using statistically-based data mining techniques in my PhD dissertation, I needed a good "Quick Course" in factor analysis. More important than just "what is factor analysis", I needed to know how to implement my ideas in SAS. This book did the trick. Now let's hope my advisors think so. :)

This book does an outstanding job of taking someone that is somewhat rusty in advanced multivariate techniques and turning them into a conversant and competent modeler. Larry Hatcher uses plain English to explain what a technique may be used for, what the required SAS code is, what the output should look like, and how the output can be interpreted. I'd strongly recommend this book for anyone taking a structural equation modeling course or wishing to apply this technique in research.

This is a great book for anyone interested in modeling dynamic systems. The authors provide wonderful background theory as a basis for building computer simulations. The simple step-by-step instructions guide you through the process of creating your own simulations using StarLogo. This book is an interesting, easily understandable beginner's manual and comes with all the software you need. It's a great way to teach yourself or other people how to program a simulation. I love the turtles!

This is a great book for people intereted in modeling systems behavior. The authors give an excellent background summary of the theory involved in StarLogo. The program given with the CD is easy to install and use. The book takes you step by step through thinking about and creating your own computer simulation in an easy to understand manner. There's lots of support for any technical difficulties you might have and good examples of what you can do with the program. I highly recommend it to everyone.

Creative
Clear
Consistent
Cost little

Most software "companions" (more than a manual...not quite a book) really do not do justice to the software. Quite the contrary for the AMPL guide. AMPL (the language) is a *very* powerful and *very* easy to use Optimization package. It interfaces with most of the major solvers. Users program in AMPL which is more or less pseudocode and then solve LP, nonlinear, combinatorial, integer, etc. programs. Unlike most software packages, it is both robust and easy to use. Likewise with the companion/book. There are many great, easy to follow examples, and it clearly explains the intrecacies of the language. A must use software and most own book for anyone doing any optimization work.

This is an excellent introduction and tutorial for the analytic element method. The book works through basic concepts in an easy readable manner without over simplification. The method is introduced and developed in a logical fashion. The discussions are involved enough for use as an ongoing reference. The included demo GFLOW however superseeded by the free demo available on the web. Every hydrogeologist should be able to understand and use the method in their toolbox, and this is a very usefull text.

This book makes the difficult mathematics behind analytic element modeling understandable. It also includes a good review of the basics of groundwater flow. Highly readable. All in all, a great introduction to AE modeling.

One of the great features of this book is that it is addressed to the empirical researcher and it really tells you how to conduct good data-analysis with longitudinal data. It doesn't push one particular piece of software, either, but uses a variety of different software packages. The book is really easy to read, and clearly explained -- and, there's so much in it!

This is a great book, it tells you in a straightforward way how to analyze your longitudinal data to answer questions of critical importance in the social sciences. It's not wedded to one particular piece of software, as many books on statistical topics are, but uses examples of real data and different software (HLM, MLwiN, SAS, Stata) to conduct the analyses. An absolute must for the researcher who collects longitudinal data.

I would highly recommend this book for users that have to create assemblies. It is the best book out there using SolidWorks. The book provides a step-by-step approach that is great. The book addresses: top-down design, in-context mates, redefining external references, renaming parts, menus, commands, importing Autocad files, drawings etc. It is packed with go and useful information. PS: And you can understand it!

My company switched from Autocad to SolidWorks 6 months ago. Assemblies were giving us a challenge. I would highly recommend this book for users that have to create assemblies. The authors step you through real issues - importing Autocad files, renaming parts, drawings with configuration, top-down design, in-context mates and redefining external references. The CD with the book contains real parts and assemblies from SolidWorks 3D collaborative web site. The tables and tips are also helpful.

Wind it till it breaks, and back off one, eh Bill? : )
Any thoughts on Project Helios (You and Bob Boucher did Sunrise II)?
Last Gasps...Exam is over.

I'd rate it pretty high, as I wrote it :-) It is book 2 in a three-book series on how to get started in building model aircraft ( rubber-powered ) The original Sky Bunny disappeared at 13 minutes + at Shafter Airport...

The first book is called The Peck ROG and the Third The Flying Aces Moth. They have been out of print for some time. You have made a real find here! I'd get one...and keep your eyes open for the other two.

If you like model aircraft, this one is priceless.

I don't get anything out of it, by the way!

Bill Warner