Bootstrap

This book is loaded with good text book examples and covers a wide variety of bootstrap applications. It is great as a reference book on the bootstrap or as a course text at a graduate level. Chernick (1999) is a little more up-to-date and covers the classifcation error rate estimation problem that is not addressed in this text. Chernick (1999) also has many more references. Efron and Tibshirani (1993) is another fine text that is a little more intuition based with less mathematics. Fieller's problem with ratio estimation and some other gems are well covered in Efron and Tibshirani but not here. Davison and Hinkley do the best job on time series of any of the bootstrap books with details about moving block bootstrap and some interesting applications.

This book has an excellent ballance between practice and theory. It presents the bootstrap as the powerful tool it is through the ellucidation of practical issues. I strongly recommend this book for everyone interested in improving statistical practice.

Relevant and clear in explanations throughout.

I counsel people on growing medicinal herbs commercially and this is the number one book I recommend to people considering starting a herb business. Lee Sturdivant provides inspirational stories from successful herb businesses around the nation. Tim Blakley provides an extensive listing of a wide variety of popular medicinal herbs and the most up-to-date information on how to grow them. Harvesting, packaging, and marketing information is also provided. Excellent book! I hope the authors will keep this one updated for us.

This is an amazing book. When my husband and I began to consider the cultivation of medicinal herbs as a retirement project, The Bootstrap Guide was recommended to us by Heather McNeill of Frontier Herbs, a major medicinal herb marketer.

The Bootstrap Guide to Medicinal Herbs exceeded my expectations. In addition to an overview of the medicinal herb industry, there are profiles of growers and herbal product manufacturers, growing requirements, and detailed instructions for propagation, cultivation, harvesting, and marketing, including questionaires filled out by herb marketing companies such as Frontier and Celestial Seasonings. These questionaires alone are worth the price of the book, giving such information as minimum purchase quantities, preference for fresh or dried, organic or non-organic, and market projections.

In addition, there is a thorough discussion of the ethics of wildcrafting and the need to develop domesticated sources for the many herbs whose popularity has made them endangered species. All this in a friendly, concise, well-written 318 pages.

If herb-growing or market gardening forms a part of your life, or your plans, read this book.

Of course, anyone who has actually read the book will know that Villanueva is from a Puerto Rican family, not a Mexican one.

Not that it matters. This is an important book for anyone in English studies, not just rhetoric & composition. Read it now.

This is a true story of the prejudice that Mexicans and people of color face in school and and in life. Luckily, he found a teacher who understood him, and gave him hope. Today, Victor Villanueva is a leader of his field, but still many people who would accept him if he was white, will not accept him because of his Mexican heritage.

This book provides a very clear treatment of model selection, the bootstrap and the computer-intensive philosophy. It places heavy emphasis on the bootstrap and cross validation. Other computer-intensive methods such as MCMC methods, multiple imputation and permutation methods are not treated. It represents development up to 1994 in a rapidly advancing area. There have been many additional theoretical and applied advances since then. It covers most of the topics of other competing books on bootstrap and resampling but is unique in its treatment of model selection and validation. It appears to require intermediate level knowledge of mathematics and freely uses matrix algebra. There are many good references and examples. The author uses FORTRAN to implement the methods and provides code. This may be a bit old fashioned.

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.

This book provides a good coverage of the very useful bootstrap method. However, post-graduation as an engineer, I find that the method is neither well known nor happily accepted by engineers outside of academia. In the corporate world, bootstrapping is left up to degreed statisticians, as this is what management trusts. As a mechanical engineer, I find that simpler statistical techniques, even if they include broad assumptions, are much more widely accepted. If you are an engineer, leave this up to the statisticians. If you are a statistician, this book is an acceptable source for learning bootstrap.

This is the best book to learn about the bootstrap. Clear style, no empty verbiage, good problems, excellent examples are some of the qualities that make this exposition of Bootstrap great. The math level is minimal - some basic statistics (perhaps at the level of Wackerly et al's book) - is all that's required.

Brad Efron wrote the key paper rediscovering the bootstrap and putting it in its proper place with other resampling techniques in his famous 1979 paper in the Annals of Statistics. His work was a breakthrough that has now led to hundreds of other publications and several books on the bootstrap and more general resampling procedures by himself, his students and many other statisticians. In fact I am working on a book with goals similar to what he and Rob Tibshirani achieve in this monograph. It is a concise and accurate presentation of the bootstrap and its wide variety of applications and is very much up to the state-of-the-art in this rapidly growing area of statistics. It is written in an intuitive fashion and avoids much of the mathematics (Edgeworth expansions etc.) which are needed to provide formal proof that the bootstrap does what it is intended to do. Provides most of the important references up through 1993. For a similar treatment that is more current, see Davison and Hinkley (1997). Bootstrap Methods and their Application. Those interested in the theory and formal mathematics should consult Hall (1992). The Bootstrap and Edgeworth Expansion.

Wish I would have read this book when I started my business.
Presents logical plan to act, rather than react, to the problems
or situations that a new business owner must confront to succeed.
A true guide to making a new business work

Kenneth Hess was the founder and President of Banner Blue Software which he took from a raw "bootstrap" startup and build it into an established company with a multimillion dollar annual sales record. Bootstrap: Lessons Learned Building A Successful Company From Scratch is the author's true story of successfully creating his viable business from scratch. Filled with risks, rewards, lessons learned the hard way and the fruits of up-close and personal inspiration, Bootstrap is an inspiring read filled with the wisdom that comes from earned experience. Strongly recommended reading for all entrepreneurs aspiring towards achieving corporate success with their own business enterprises, regardless of services furnished or products produced.

I thoroughly enjoyed reading this book, for a multitude of reasons. Ken details the entrepreneur's issues when bootstrapping a company quite well (we bootstrapped our company also, and ran into many of the same problems). I enjoyed reading more about how Ken FELT while the company was growing. As an employee, you don't often know how the CEO feels about anything (Ken is good at controlling his emotions). Turns out he had similar feelings most entrepreneur's do when starting a company.

The book is engrossing and at times reads like a story. Sometimes it's hard to believe, but I know it happened because I had the fortune of living through part of it. I highly recommend this book to anyone that wants to be successful at building a company. I'm convinced that the "Banner Blue Way" is the way to run a company and run a short-term project. Many companies later, I'm still running things the way Ken would have done it.

I found this book rather interesting, with a nice mix of methods and applications. I intended to use some of the examples in a course that I am teaching. There are many examples given which use data sets to illustrate important concepts. However, I was unable to access several of these data sets. I contacted the author and mentioned that I was particularly interested in accessing two of the data sets that were referenced in the book --- his reply was that data sets for the book were available at a specific URL. Indeed there were several data sets at this location; but, not the data sets that I had mentioned in my inquiry.

I did a lot of searching on my own for these data sets. One of these supposedly came from Sweden; but, after extensive searching through several Swedish databases I found nothing on this particular data set. I contacted the author again and requested at least a reference or link to these data sets --- no reply to my request has been received (after 11 days).

I feel strongly that all data sets referenced in a book of this type should be available to the readers. If not, then they should not be used in examples.

Manly is an excellent writer who has written several excellent texts and is an editor of a biostatistics journal. This is a revision of a very popular text on randomization or permutation methods. Because of the immense popularity of bootstrap methods (a similar resampling procedure), he elected to add some coverage of the bootstrap. All topics are covered in a clear and scholarly style and examples from biology are given. The interested reader might also look at Good (2000), Permutation Methods, 2nd Edition, published by Springer-Verlag and Edgington, Randomization Tests published by Marcel Dekker for other accounts on permutation tests. There are now several good books dedicated to bootstrap methods including Davison and Hinkley (1997), Cambridge University Press, Efron and Tibshirani (1993), CRC-Chapman and Hall and Chernick (1999), John Wiley and Sons, Inc.

Statistical analysis based on resampling methods are clearly the way the bulk of statistics should be done, and the trend is towards this. Manly gives an excellent and clear treatment introducing these methods in various settings in population biology. This book is clearly a must for any biologist that has to deal with data, and it should be read by all such biologist. I shamelessly copy from this book when I present resampling methods to my graduate biostatistics class.

Michael Chernick ... has written this book which may be considered as a first complete account of the Bootstrap methods since Efron's seminal paper in 1979. Chernick has used the Current Index to Statistics CD ROM, and several other search engines ... to collect all journal papers and books that have any relation with the Bootstrap. The result is a list of 1600 references of which more than 600 are actually cited in his book. Apart from this, I found his book interesting to read, especially his sections on the error rate estimation in two-class discrimination problems leading to the so-called .632 estimator (which is one of the big succes stories for the bootstrap), and the applications of bootstrapping in Kriging, analysis of mixture models, censored data analysis, missing data problems, and Bayesian bootstrapping. Finally he devotes a chapter on situations when Bootstrapping might fail, such as in the case of extreme value estimation.

Anyone with a serious interest in resampling will want to have this book in his or her library. The reference listings, invaluable for researchers, are the most complete currently available for bootstrappers. The material is accessible to applied workers, with mathematical complexity kept at a minimum. Bootstrapping, when approached in the right way, is a tool of great general testing application and minimal complexity. Chernick's book keeps things clear and accessible. This is the right reference book published at the right time.

This is a review of the sample page, which misspells "bootstrap" as "bootstap" and does not predispose me to buy the book!

I do a great deal of number mashing especially for time series data. Although a Gaussian assumption is typical for a variety of reasons the really interesting stuff (IMHO) is where K.F.G.'s theory drops the ball. The GLD and its variations is very flexible in 'fitting' distributions. The exposition in this book has sufficient clarity as well as numerous examples. It is definitely slanted towards applications although there is sufficient theory that a strict empiricist can confuse themselves if they so choose. The theory is presented in a manner that I was able to 'translate' it into an EXCEL/VB application. The examples were sufficient to provide checks on the translation. Some code is also included in the book but it is for an application I do not use. Also, there are extensive tables of 'nominal' lambda values given various moments and/or quantile representations. ... In short, IMHO, the GLD should be in every numerical toolbox and the book should be on one's shelf. Good Stuff!