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

Contributor(s): Material type: TextTextLanguage: English Publication details: New York : Oxford University Press, 2014.Description: xviii, 539 p. ; 26 cmISBN:
  • 9780199857944
Subject(s): DDC classification:
  • 330.015195 RAC
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.
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Item type Current library Collection Shelving location Call number Status Barcode
Reference Reference Kalaignar Centenary Library Madurai ENGLISH-REFERENCE BOOKS நான்காம் தளம் / Fourth floor 330.015195 RAC (Browse shelf(Opens below)) Not for loan 269692

Includes bibliographical references and index.

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.

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