Discrete Choice Methods with Simulation

If I could give this book six stars I would. It's simply one of the best statistics books I've ever read.This book is very well-written by one of the experts in the field. It covers logit models and the various generalizations (GEV, mixed logit, probit, etc.) in detail, along with a thorough discussion of modern estimation of these models. What I find most useful about it is that the words-to-equations density is highly favorable. The equations you need are there, but the words you need are there too, making sure you understand the model assumptions inside and out. Each equation is explained thoroughly and the surrounding discussion probes the model to bring the reader to a critical understanding of what exactly is implied by the model. Too often complex statistical models are treated in a "black box" fashion. The dirty little secret is that it's easier for the author to do this. Train doesn't take the easy way out. The fact that his web site has truly excellent support--including a large number of webinars in addition to the more usual papers, software, etc.--makes this book a doubly valuable item. See [...] for even more.

Really comes in handy, easy to read but plenty of detail too. Holds up well to in-depth scrutiny and very broad coverage of MDC.

Fantastic book even if you aren't actually that interested in logit, probit, etc. Just the crystal clear parts on numerical optimization and simulation are worth the price.

Classics and a must have for anyone who does or aspires to do any structural work in Economics or Marketing.

The book is excellent for guys on discrete choice models and analysis. It has good structure to show how model is developed and provides the estimation methods.

Great

As a previous reviewer has already stated, this may quite possibly be the best statistics/econometrics book. It's not a textbook with end-of-chapter problems covering hundreds of topics. It's more of an in-depth narrative on the single important subject of discrete choice models (e.g., logit, probit, and many advanced extensions). The reader should have a background in statistics at the level of Casella & Berger's text. So this book is great for researchers and graduate students in math, stats, engineering, and economics, but is probably too advanced for those in psych, polysci, and sociology. If you're even thinking about doing some sort of discrete choice analysis, this book is a must read. It's extremely insightful, and Train's ability to explain everything in both mathematical and non-technical terms is astonishing. Everytime I think to myself "I wonder what situation would fit here," Train never fails to give a concise, informative example. If his teaching style is anything like what is in this book, it may be worth taking a leave from UCSD to visit Berkeley for a semester just to take his class.

Excelente book

ここ10年ほどに発展してきたDiscrete Choiceの手法を非常に分かりやすく説明する良書です。Discrete choiceのテキストといえばMaddala(1983)を推す人が多いようですが、本書の優れている点は上述した最近この分野の成果(Mixed logitなど)を網羅し、それらを実際に使用する上で必要になってくるSimulationの方法を紹介しているところです。この本を一読した上で関連する論文にあたってみると格段に理解が進むと思われます。ただ、Maddalaに比べ、数学的に厳密な議論はなされていない、出てくる例がI.Oに関するものばかり、という欠点はあると思います。しかし、それらの欠点を加味しても、難解で理解に時間がかかるであろうDiscrete choiceの最新の手法をコンパクトにクリアーに、そして具体的に解説しており、まさに｢痒いところに手が届く｣一冊です。