The Oxford handbook of applied nonparametric and semiparametric econometrics and statistics / edited by Jeffrey Racine, Liangjun Su, and Aman Ullah.

Contributor(s):

Material type: Text

TextSeries: Oxford handbooksPublisher: Oxford : Oxford University Press, [2014]Description: 1 online resource (xviii, 539 pages) : illustrationsContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9780199857951
0199857954
9781306168472
1306168473

Subject(s): Genre/Form:

Additional physical formats: Print version:: Oxford handbook of applied nonparametric and semiparametric econometrics and statistics.DDC classification:

330.01/5195 23

LOC classification:

HB139 .O96 2013eb

Online resources:

Click here to access online

Contents:

Part I. Methodology -- part II. Inverse problems -- part III. Additive models -- part IV. Model selection and averaging -- part V. Time series -- part VI. Cross section.

Summary: This volume, edited by Jeffrey Racine, Liangjun Su, and Aman Ullah, contains the latest research on nonparametric and semiparametric econometrics and statistics. These data-driven models seek to replace the ""classical"" parametric models of the past, which were rigid and often linear. Chapters by leading international econometricians and statisticians highlight the interface between econometrics and statistical methods for nonparametric and semiparametric procedures. They provide a balanced view of new developments in the analysis and modeling of applied sciences with cross-section, time seri.

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Item type	Home library	Collection	Call number	Materials specified	Status	Date due	Barcode
Electronic-Books	OPJGU Sonepat- Campus	E-Books EBSCO			Available

Series from print version book jacket.

Includes bibliographical references and indexes.

Print version record.

Part I. Methodology -- part II. Inverse problems -- part III. Additive models -- part IV. Model selection and averaging -- part V. Time series -- part VI. Cross section.

This volume, edited by Jeffrey Racine, Liangjun Su, and Aman Ullah, contains the latest research on nonparametric and semiparametric econometrics and statistics. These data-driven models seek to replace the ""classical"" parametric models of the past, which were rigid and often linear. Chapters by leading international econometricians and statisticians highlight the interface between econometrics and statistical methods for nonparametric and semiparametric procedures. They provide a balanced view of new developments in the analysis and modeling of applied sciences with cross-section, time seri.

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