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Central Limit Theorem for Asymmetric Kernel Functionals

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Author Info
Fernandes, M.

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Abstract

Asymmetric kernels are quite useful for the estimation of density functions which have bounded support. Gamma kernels are designed to handle density functions whose supports are bounded from one end only, whereas beta kernels are particularly convenient for the estimation of density functions with compact support. This paper extends the central limit theorem for degenerate U-statistics in order to compute the limiting distribution of certain asymmetric kernel functionals.

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Publisher Info
Paper provided by European University Institute in its series Economics Working Papers with number eco2000/1.

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Length: 18 pages
Date of creation: 2000
Date of revision:
Handle: RePEc:eui:euiwps:eco2000/1

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Keywords: STATISTICS ; MATHEMATICS;

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Find related papers by JEL classification:
C60 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - General
C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

References listed on IDEAS
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  1. Chen, Song Xi, 1999. "Beta kernel estimators for density functions," Computational Statistics & Data Analysis, Elsevier, vol. 31(2), pages 131-145, August. [Downloadable!] (restricted)
  2. Song Chen, 2000. "Probability Density Function Estimation Using Gamma Kernels," Annals of the Institute of Statistical Mathematics, Springer, vol. 52(3), pages 471-480, September. [Downloadable!] (restricted)
  3. Ait-Sahalia, Yacine & Bickel, Peter J. & Stoker, Thomas M., 2001. "Goodness-of-fit tests for kernel regression with an application to option implied volatilities," Journal of Econometrics, Elsevier, vol. 105(2), pages 363-412, December. [Downloadable!] (restricted)
  4. Bruce M. Brown, 1999. "Beta-Bernstein Smoothing for Regression Curves with Compact Support," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association and Swedish Statistical Association, vol. 26(1), pages 47-59. [Downloadable!] (restricted)
  5. Fernandes, Marcelo & Grammig, Joachim, 2005. "Nonparametric specification tests for conditional duration models," Journal of Econometrics, Elsevier, vol. 127(1), pages 35-68, July. [Downloadable!] (restricted)
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  1. BOUEZMARNI, Taoufik & ROMBOUTS, Jeroen V. K., 2006. "Nonparametric density estimation for positive time series," CORE Discussion Papers 2006085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
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  2. Fernandes, Marcelo & Grammig, Joachim, 2003. "Nonparametric specification tests for conditional duration models," Economics Working Papers (Ensaios Economicos da EPGE) 502, Graduate School of Economics, Getulio Vargas Foundation (Brazil). [Downloadable!]
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