1 item has been added to your cart.
Quantile Regression |
||||||||||||||||||||||||||||||||||||||
 Click to enlarge See the back cover |
As an Amazon Associate, StataCorp earns a small referral credit from
qualifying purchases made from affiliate links on our site.
VitalSource eBook details
VitalSource eBooks are read using the Bookshelf How to access your eBook1) Visit Bookshelf online to sign in or create an account.
2) Once logged in, click redeem in the upper right corner. Enter your eBook code. Your eBook code will be in your order confirmation email under the eBook's title.
3) The eBook will be added to your library. You may then download Bookshelf on other devices and sync your library to view the eBook.
Bookshelf is available on the following:
Bookshelf allows you to have 2 computers and 2 mobile devices activated at any given time.
I was amazed at the VitalSource way of presenting the books....
Everything looks perfectly typeset, but yet you can "flip"
through the book in the same way you would "flip" through a very
long web page in your web browser. And best of all, whenever I
have my tablet with me, my books are just a swipe away.
— Michael Mitchell
Senior statistician at the USC Children's Data Network, author of four Stata Press books, and former UCLA statistical consultant who envisioned and designed the UCLA Statistical Consulting Resources website. Return policy for eBooksStata Press eBooks are nonreturnable and nonrefundable. ×eBook not available for this title |
|
||||||||||||||||||||||||||||||||||||
Comment from the Stata technical groupQuantile Regression, by Lingxin Hao and Daniel Q. Naiman, provides an excellent introduction to quantile-regression methods. The intuitive explanations and many examples make this book easy to read and understand. An appendix provides Stata commands to replicate the examples using the datasets available at http://www.ams.jhu.edu/~hao/QRbook_data_codes/. After showing the advantages that quantile regression has over least squares, the authors discuss the estimation technique, the statistical inference, and how to interpret the results. The example-based approach is exceptionally clear and avoids swamping the reader in technical details. The final section of the monograph applies the techniques to changes in U.S. income equality between 1991 and 2001. This application illustrates both how to use the methods and how to interpret the results. |
||||||||||||||||||||||||||||||||||||||
Table of contentsView table of contents >> |
||||||||||||||||||||||||||||||||||||||
 |
 |
 |
 |
 |
 |
)