This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Central limit theorem for integrated square error of multivariate nonparametric density estimators

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Hall, Peter
Abstract

Martingale theory is used to obtain a central limit theorem for degenerate U-statistics with variable kernels, which is applied to derive central limit theorems for the integrated square error of multivariate nonparametric density estimators. Previous approaches to this problem have employed Komlós-Major-Tusnády type approximations to the empiric distribution function, and have required the following two restrictive assumptions which are not necessary using the present approach: (i) the data are in one or two dimensions, and (ii) the estimator is constructed suboptimally.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.sciencedirect.com/science/article/B6WK9-4CRM9MP-9W/2/a37c769b2fb16c456a8e63ce587d35d4
File Format:
File Function:
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Publisher Info
Article provided by Elsevier in its journal Journal of Multivariate Analysis.

Volume (Year): 14 (1984)
Issue (Month): 1 (February)
Pages: 1-16
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:eee:jmvana:v:14:y:1984:i:1:p:1-16

Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description

Order Information:
Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
Web: https://shop.elsevier.com/order?id=622892&ref=622892_01_ooc_1&version=01

For technical questions regarding this item, or to correct its listing, contact: (Heidi Boesdal).

Related research
Keywords: central limit theorem integrated square error Martingale nonparametric density estimator U-statistic;

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Adonis Yatchew & Len Bos, 1997. "Nonparametric Least Squares Regression and Testing in Economic Models," Working Papers yatchew-99-01, University of Toronto, Department of Economics. [Downloadable!]
  2. Aït-Sahalia, Yacine. & Bickel, Peter J. & Stoker, Thomas M., 1994. "Goodness-of-fit tests for regression using kernel methods," Working papers 3747-94., Massachusetts Institute of Technology (MIT), Sloan School of Management. [Downloadable!]
  3. Gao, Jiti & Hong, Yongmiao, 2007. "Central limit theorems for weighted quadratic forms of dependent processes with applications in specification testing," MPRA Paper 11977, University Library of Munich, Germany, revised Dec 2007. [Downloadable!]
  4. Cheng Hsiao & Qi Li & Jeff Racine, 2006. "A Consistent Model Specification Test with Mixed Discrete and Continuous Data," IEPR Working Papers 06.47, Institute of Economic Policy Research (IEPR). [Downloadable!]
    Other versions:
  5. Taoufik Bouezmarni & Jeroen Rombouts & Abderrahim Taamouti, 2009. "A Nonparametric Copula Based Test for Conditional Independence with Applications to Granger Causality," CIRANO Working Papers 2009s-28, CIRANO. [Downloadable!]
    Other versions:
  6. Fuchun Li, 2005. "Testing the Parametric Specification of the Diffusion Function in a Diffusion Process," Working Papers 05-35, Bank of Canada. [Downloadable!]
  7. Shingo Shirahata & In-Sun Chu, 1992. "Integrated squared error of kernel-type estimator of distribution function," Annals of the Institute of Statistical Mathematics, Springer, vol. 44(3), pages 579-591, September. [Downloadable!] (restricted)
  8. Norbert Henze, 2002. "Invariant tests for multivariate normality: a critical review," Statistical Papers, Springer, vol. 43(4), pages 467-506, October. [Downloadable!] (restricted)
  9. Kyoo il Kim, 2006. "Uniform Convergence Rate of the SNP Density Estimator and Testing for Similarity of Two Unknown Densities," Working Papers 20-2006, Singapore Management University, School of Economics. [Downloadable!]
  10. Halbert White & Yongmiao Hong, 1999. "M-Testing Using Finite and Infinite Dimensional Parameter Estimators," University of California at San Diego, Economics Working Paper Series 93-01r, Department of Economics, UC San Diego. [Downloadable!]
    Other versions:
  11. Yanqin Fan & Qi Li, 2002. "A Consistent Model Specification Test Based On The Kernel Sum Of Squares Of Residuals," Econometric Reviews, Taylor and Francis Journals, vol. 21(3), pages 337-352. [Downloadable!] (restricted)
  12. Kiho Jeong & Wolfgang Härdle, 2008. "A Consistent Nonparametric Test for Causality in Quantile," SFB 649 Discussion Papers SFB649DP2008-007, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
  13. Qi Li & Esfandiar Maasoumi & Jeffrey S. Racine, 2008. "A Nonparametric Test For Equality Of Distributions With Mixed Categorical And Continuous Data," Emory Economics 0805, Department of Economics, Emory University (Atlanta). [Downloadable!]
    Other versions:
  14. L. Yang, . "Root-n Convergent Transformation-Kernel Density Estimation," Sonderforschungsbereich 373 1996-94, Humboldt Universitaet Berlin.
  15. Whitney Newey & Frank Windmeijer, 2005. "GMM with many weak moment conditions," CeMMAP working papers CWP18/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
  16. Donald W.K. Andrews & James H. Stock, 2005. "Inference with Weak Instruments," Cowles Foundation Discussion Papers 1530, Cowles Foundation, Yale University. [Downloadable!]
    Other versions:
  17. Sun, Y., 2003. "A Consistent Nonparametric Equality Test of Conditional Quantile Functions," Working Papers 2003-10, University of Guelph, Department of Economics. [Downloadable!]
    Other versions:
  18. Eduardo Fé-Rodríguez & Chris D. Orme, 2009. "On the Sensitivity of Kernel-based Tests of Conditional Moment Restrictions," The School of Economics Discussion Paper Series 0912, Economics, The University of Manchester. [Downloadable!]
  19. Stefania D'Amico, 2005. "Density selection and combination under model ambiguity: an application to stock returns," Finance and Economics Discussion Series 2005-09, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  20. Stefania D'Amico, 2004. "Density Estimation and Combination under Model Ambiguity," Computing in Economics and Finance 2004 273, Society for Computational Economics. [Downloadable!]
  21. Joris Pinkse, 2000. "Feasible Multivariate Nonparametric Estimation Using Weak Separability," Econometric Society World Congress 2000 Contributed Papers 1241, Econometric Society. [Downloadable!]
Statistics
Access and download statistics

Did you know? IDEAS is also providing many rankings, for example of authors and institutions.

This page was last updated on 2009-12-3.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.