國立虎尾科技大學 |

Quantile regression /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Quantile regression // Roger Koenker.
Author:	Koenker, Roger,
Description:	1 online resource (xv, 349 pages) :digital, PDF file(s). :
Notes:	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Subject:	Regression analysis. -
Online resource:	https://doi.org/10.1017/CBO9780511754098
ISBN:	9780511754098 (ebook)

Quantile regression /
Koenker, Roger,1947-

Quantile regression /Roger Koenker. - 1 online resource (xv, 349 pages) :digital, PDF file(s). - Econometric Society monographs ;38. - Econometric Society monographs ;49..

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

1. Introduction -- 2. Student Course Evaluations and Class Size -- 3. Inference for Quantile Regression -- 4. Asymptotic Theory of Quantile Regression -- 5. L-Statistics and Weighted Quantile Regression -- 6. Computational Aspects of Quantile Regression -- 7. Nonparametric Quantile Regression -- 8. Twilight Zone of Quantile Regression -- 9. Conclusion -- A. Quantile Regression in R : A Vignette -- B. Asymptotic Critical Values -- References -- Name Index -- Subject Index.

Quantile regression is gradually emerging as a unified statistical methodology for estimating models of conditional quantile functions. By complementing the exclusive focus of classical least squares regression on the conditional mean, quantile regression offers a systematic strategy for examining how covariates influence the location, scale and shape of the entire response distribution. This monograph is the first comprehensive treatment of the subject, encompassing models that are linear and nonlinear, parametric and nonparametric. The author has devoted more than 25 years of research to this topic. The methods in the analysis are illustrated with a variety of applications from economics, biology, ecology and finance. The treatment will find its core audiences in econometrics, statistics, and applied mathematics in addition to the disciplines cited above.

ISBN: 9780511754098 (ebook)Subjects--Topical Terms:

569541
Regression analysis.

LC Class. No.: QA278.2 / .K64 2005

Dewey Class. No.: 519.5/36

Quantile regression /
LDR:02381nam a2200313 i 4500 001 1126405
003 UkCbUP
005 20151005020622.0
006 m|||||o||d||||||||
007 cr||||||||||||
008 240926s2005||||enk o ||1 0|eng|d
020 $a 9780511754098 (ebook)
020 $z 9780521845731 (hardback)
020 $z 9780521608275 (paperback)
035 $a CR9780511754098
040 $a UkCbUP $b eng $e rda $c UkCbUP
050 0 0 $a QA278.2 $b .K64 2005
082 0 0 $a 519.5/36 $2 22
100 1 $a Koenker, Roger, $d 1947- $e author. $3 1445200
245 1 0 $a Quantile regression / $c Roger Koenker.
264 1 $a Cambridge : $b Cambridge University Press, $c 2005.
300 $a 1 online resource (xv, 349 pages) : $b digital, PDF file(s).
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
490 1 $a Econometric Society monographs ; $v 38
500 $a Title from publisher's bibliographic system (viewed on 05 Oct 2015).
505 0 $a 1. Introduction -- 2. Student Course Evaluations and Class Size -- 3. Inference for Quantile Regression -- 4. Asymptotic Theory of Quantile Regression -- 5. L-Statistics and Weighted Quantile Regression -- 6. Computational Aspects of Quantile Regression -- 7. Nonparametric Quantile Regression -- 8. Twilight Zone of Quantile Regression -- 9. Conclusion -- A. Quantile Regression in R : A Vignette -- B. Asymptotic Critical Values -- References -- Name Index -- Subject Index.
520 $a Quantile regression is gradually emerging as a unified statistical methodology for estimating models of conditional quantile functions. By complementing the exclusive focus of classical least squares regression on the conditional mean, quantile regression offers a systematic strategy for examining how covariates influence the location, scale and shape of the entire response distribution. This monograph is the first comprehensive treatment of the subject, encompassing models that are linear and nonlinear, parametric and nonparametric. The author has devoted more than 25 years of research to this topic. The methods in the analysis are illustrated with a variety of applications from economics, biology, ecology and finance. The treatment will find its core audiences in econometrics, statistics, and applied mathematics in addition to the disciplines cited above.
650 0 $a Regression analysis. $3 569541
650 0 $a Mathematical statistics. $3 527941
776 0 8 $i Print version: $z 9780521845731
830 0 $a Econometric Society monographs ; $v 49. $3 1133549
856 4 0 $u https://doi.org/10.1017/CBO9780511754098