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An Information theoretic approach to...

Judge, George G.

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An Information theoretic approach to econometrics /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	An Information theoretic approach to econometrics // George G. Judge, Ron C. Mittelhammer.
作者:	Judge, George G.
其他作者:	Mittelhammer, Ron.
出版者:	Cambridge :Cambridge University Press, : 2012.,
面頁冊數:	xvi, 232 p. :ill., figures ;23 cm.
標題:	Econometrics. -
電子資源:	http://site.ebrary.com/id/10533151
電子資源:	http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=432727
電子資源:	http://dx.doi.org/10.1017/CBO9781139033848
ISBN:	0521689732 (pbk.)

An Information theoretic approach to econometrics /
Judge, George G.

An Information theoretic approach to econometrics /George G. Judge, Ron C. Mittelhammer. - Cambridge :Cambridge University Press,2012. - xvi, 232 p. :ill., figures ;23 cm.

Includes bibliographical references and index.

"This book is intended to provide the reader with a firm conceptual and empirical understanding of basic information-theoretic models and methods. Because most data are observational, practitioners work with indirect noisy observation and ill-posed econometric in the form of stochastic inverse problems. Consequently, traditional econometric methods in many cases are not applicable for answering many of the quantitative questions that analysts wish to ask. After initial chapters deal with parametric and semiparametric linear probability models, the focus turns to solving nonparametric stochastic inverse problems. In succeeding chapters, a family of pwer divergence measure-likelihood functions are introduced for a range of traditional and nontraditional econometric-models problems. Finally, within either an empirical maximum likelihood or loss context, Ron C. Mittelhammer and George G. Judge suggest a basis for choosing a member of the divergence family"--

ISBN: 0521689732 (pbk.)Subjects--Topical Terms:

542934
Econometrics.

LC Class. No.: HB139 / .J795 2012eb

Dewey Class. No.: 330.01/5195

An Information theoretic approach to econometrics /
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245 1 0 $a An Information theoretic approach to econometrics / $c George G. Judge, Ron C. Mittelhammer.
260 # $a Cambridge : $b Cambridge University Press, $c 2012.
300 $a xvi, 232 p. : $b ill., figures ; $c 23 cm.
504 $a Includes bibliographical references and index.
520 # $a "This book is intended to provide the reader with a firm conceptual and empirical understanding of basic information-theoretic models and methods. Because most data are observational, practitioners work with indirect noisy observation and ill-posed econometric in the form of stochastic inverse problems. Consequently, traditional econometric methods in many cases are not applicable for answering many of the quantitative questions that analysts wish to ask. After initial chapters deal with parametric and semiparametric linear probability models, the focus turns to solving nonparametric stochastic inverse problems. In succeeding chapters, a family of pwer divergence measure-likelihood functions are introduced for a range of traditional and nontraditional econometric-models problems. Finally, within either an empirical maximum likelihood or loss context, Ron C. Mittelhammer and George G. Judge suggest a basis for choosing a member of the divergence family"-- $c Provided by publisher.
650 # 0 $a Econometrics. $3 542934
650 # 0 $a Economics. $3 517137
650 # 7 $a Business & economics / Econometrics $2 bisacsh $3 1622593
650 # 7 $a Business & economics / Statistics $2 bisacsh $3 1622594
700 1 # $a Mittelhammer, Ron. $3 703124
856 4 0 $3 ebrary $u http://site.ebrary.com/id/10533151
856 4 0 $3 EBSCOhost $u http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=432727
856 4 0 $3 Cambridge Books Online $u http://dx.doi.org/10.1017/CBO9781139033848