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Bootstrap tests for regression models

Godfrey, L. G.

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Bootstrap tests for regression models

Record Type:	Electronic resources : Monograph/item
Title/Author:	Bootstrap tests for regression models/ Leslie Godfrey.
Author:	Godfrey, L. G.
Published:	Basingstoke, Hampshire ;Palgrave Macmillan, : 2009.,
Description:	xiii, 329 p. ;22 cm.
[NT 15003449]:	Tests for linear regression models -- Simulation-based tests : basicideas -- Simulation-basedtests for regression models with IID errors : some standard cases -- Simulation-based tests for regression models with IID errors : some non-standard cases -- Bootstrap methods for regression models with non-IID errors -- Simulation-based tests for regression models with non-IID errors -- Simulation-Based Tests for Non-Nested Regression Models.
Subject:	Bootstrap (Statistics) -
Online resource:	http://link.springer.com/10.1057/9780230233737access to fulltext (Palgrave)
ISBN:	0230233732

Bootstrap tests for regression models
Godfrey, L. G.

Bootstrap tests for regression models[electronic resource] /Leslie Godfrey. - Basingstoke, Hampshire ;Palgrave Macmillan,2009. - xiii, 329 p. ;22 cm. - Palgrave texts in econometrics. - Palgrave texts in econometrics..

Includes bibliographical references (p. 305-317) and indexes.

Tests for linear regression models -- Simulation-based tests : basicideas -- Simulation-basedtests for regression models with IID errors : some standard cases -- Simulation-based tests for regression models with IID errors : some non-standard cases -- Bootstrap methods for regression models with non-IID errors -- Simulation-based tests for regression models with non-IID errors -- Simulation-Based Tests for Non-Nested Regression Models.

Modern computer systems are now so powerful that they can be used tocarry out simulation-based statistical investigations without involving delays or the need to access high levels of equipment. When carrying out econometric analyses, the routine use of computer-based methods offers a valuable alternative to the standard approach in which approximations are based upon what happens as the sample size grows without limit. Applied work has to be based upon a finite number of observations. Computationally-intensive techniques and, in particular, bootstrap methods provide ways to improve thefinite-sample performance of well-known tests. Bootstrap tests can also be employed when conventional theory does not lead to a test statistic, which can be compared with critical values from some standard distribution. This book uses the familiar linearregression model as a framework for introducing simulation-based teststo applied workers, students and others who carry out empirical econometricanalyses. .

Electronic reproduction.
Basingstoke, England :
Palgrave Macmillan,
2010.

Mode of access:World Wide Web.

ISBN: 0230233732

Standard No.: 10.1057/9780230233737doiSubjects--Topical Terms:

565960
Bootstrap (Statistics)
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: HB141 / .G63 2009

Dewey Class. No.: 330.01/519536

Bootstrap tests for regression models
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245 1 0 $a Bootstrap tests for regression models $h [electronic resource] / $c Leslie Godfrey.
260 $a Basingstoke, Hampshire ; $a New York, NY : $c 2009. $b Palgrave Macmillan,
300 $a xiii, 329 p. ; $c 22 cm.
490 1 $a Palgrave texts in econometrics
504 $a Includes bibliographical references (p. 305-317) and indexes.
505 0 $a Tests for linear regression models -- Simulation-based tests : basicideas -- Simulation-basedtests for regression models with IID errors : some standard cases -- Simulation-based tests for regression models with IID errors : some non-standard cases -- Bootstrap methods for regression models with non-IID errors -- Simulation-based tests for regression models with non-IID errors -- Simulation-Based Tests for Non-Nested Regression Models.
520 $a Modern computer systems are now so powerful that they can be used tocarry out simulation-based statistical investigations without involving delays or the need to access high levels of equipment. When carrying out econometric analyses, the routine use of computer-based methods offers a valuable alternative to the standard approach in which approximations are based upon what happens as the sample size grows without limit. Applied work has to be based upon a finite number of observations. Computationally-intensive techniques and, in particular, bootstrap methods provide ways to improve thefinite-sample performance of well-known tests. Bootstrap tests can also be employed when conventional theory does not lead to a test statistic, which can be compared with critical values from some standard distribution. This book uses the familiar linearregression model as a framework for introducing simulation-based teststo applied workers, students and others who carry out empirical econometricanalyses. .
533 $a Electronic reproduction. $b Basingstoke, England : $c Palgrave Macmillan, $d 2010. $n Mode of access:World Wide Web. $n System requirements: Web browser. $n Title from title screen (viewed on Jan. 11, 2010). $n Access may be restricted to users at subscribing institutions.
650 0 $a Bootstrap (Statistics) $3 565960
650 0 $a Econometric models. $3 542933
650 0 $a Regression analysis. $3 529831
655 7 $a Electronic books. $2 lcsh $3 542853
710 2 $a Palgrave Connect (Online service) $3 1081578
830 0 $a Palgrave texts in econometrics. $3 1097965
856 4 0 $3 Palgrave Connect $u http://link.springer.com/10.1057/9780230233737 $z access to fulltext (Palgrave)