I want a book that have programs for the T-83, and the must importent thing I want to know how to programs games on my carculator.

Brad Efron wrote this monograph shortly after the publication of his groundbreaking early papers on bootstrapping. It was the first and for many years the only major reference on bootstrapping. It is written in an intuitive style and provides the connection between the bootstrap and many of the other earlier resampling methods, especially the jackknife. Geometric arguments are often used to explain concepts. Today it is still a useful reference but is very much outdated as there have been many advances. There are now also several excellent reference books and texts on the bootstrap including the introductory text by Efron and Tibshirani published in 1993 and the text by Davison and Hinkley published in 1997. My book published by Wiley in 1999 is intended for practitioners and has over 1600 references.

I've been reading the general linear model section all day today, and it is just so nicely written I thought I needed to write a review. I can't imagine a clearer and more succinct description of this difficult topic. Entirely understandable, but be prepared to read chapters from beginning to end as unexpected abbreviations are often introduced and carried throughout the chapter.

As with all of the Kendall Advanced Theory books, a moderate degree of mathematical sophistication is assumed.

Classification is a favorite topic of Krzanowki and is one of the topics covered in this volume. This is part 2 of a volume on multivariate analysis in the Kendall's Library of Statistics series. So it has the flavor and feel of the Advanced Theory in Statistics books, a concise but almost encyclopediac treatment of advanced topics. In the first chapter on discriminant analysis (chapter 9 of this 2 volume text) time is spent describing the various methods of error rate estimation including the bootstrap and the key simulation studies of Efron, Chatterjee and Chatterjee, Snapinn and Knoke, Jain et al.,and Ganeshanandam and Krzanowski are all mentioned and referenced. There is even a section on neural networks.

The related topic of cluster analysis is covered in Chapter 10. Chapter 11 covers covariance and interaction structures that includes log-linear models, hierarchical conditional Gaussian models, path analysis and regression models. Chapter 12 covers latent structure models including factor analysis. Chapter 13 covers repeated measures and growth curve models, popular topics under a great deal of research activity lately, particularly in the pharmaceutical industry. Chapter 14 on miscellaneous topics includes shape analysis, functional data, distance measures between populations, and circular and spherical data.

(From the view point of an economist only) Don't know a thing about kernel smoothing? No problem! This book brilliantly explains the idea of kernel smoothing using English! (You remember how advanced econometrics quickly become an alien language.), with minimum requirement on econometrics.It is a must buy if you are working on this subject.

This is the definitive book in the new mushrooming mathematical field of large deviations, which everybody should know including mathematicians, physical scientists, social and behavioral scientists, life scientists, etc. Large deviations refers to rare and extreme events, which are studied by examining the extreme ends or "tails" of graphs (which is where graphs usually get narrower and narrower). My own research is also largely in the field of rare events, but I study them more directly by using logic-based probability, defined as the probability of the set/event analogue of the logical conditional A-->B = A' U B (see abstracts of about 35 of my papers at the Institute for Logic of the University of Vienna, available on the internet). Dembo and Zeitouni study rare events by more standard methods, but the results make fascinating reading and give ideas for all kinds of research. This type of research differs from the usual preoccupation of scientists with common events, frequent events, average events, and so. It has become obvious that the rare events, such as great genius, great discoveries and creativity, accidental events, catastrophes, and so on, play an extremely important role in the world. Dembo and Zeitouni are examples of the best in Israeli research, although they have never responded to my inquiries (perhaps they are too busy being great geniuses).

Most statistics books are written for math wizards and can hardly be understood by others. This book explains a number of statistical methods, such as factor analysis, path analysis, and structural equation models, and does so in ways that are clear, easy to grasp, and with fuly-worked examples. I learned more about statistics from this one book than all the others I've read combined.

This book starts with an introduction to ergodic theory. The rest of the book is on absolutely continuous invariat measures and their applications. This is one of the best books that studies conditions of existance of absolutely continuous invariat measures for piecewise expanding maps.

This book provides a nice introduction to the mathematical theory of rare events and extreme values. It takes the point process approach to rare events using the empirical point process defined by the crossing of a high or low level to employ an approximate Poisson process. This approach has broad applicability and the authors use it to consider rare and extreme events for stochastic processes including Gaussian processes, Poisson point processes, extreme value models and nonparametric regression.

This book is noteworthy for its mix of theory and application and for the introduction of the software XTREMES. Chapter 6 is devoted to explaining how to analyze data for extremes using the software XTREMES. A diskette is included with the text with version 1.2 of XTREMES that is an interactive program that can run on MS-DOS operated computers. The text is very much up-to-date on the theoretical developments as of 1994.