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A Simple Deconvolving Kernel Density Estimator when Noise is Gaussian

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Author Info
Isabel Proenca (ISEG-UTL)

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Abstract

Deconvolving kernel estimators when noise is Gaussian entail heavy calculations. In order to obtain the density estimates numerical evaluation of a specific integral is needed. This work proposes an approximation to the deconvolving kernel which simplifies considerably calculations by avoiding the typical numerical integration. Simulations included indicate that the lost in performance relatively to the true deconvolving kernel, is almost negligible in finite samples.

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File URL: http://129.3.20.41/eps/em/papers/0508/0508006.pdf
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Publisher Info
Paper provided by EconWPA in its series Econometrics with number 0508006.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 9 pages
Date of creation: 05 Aug 2005
Date of revision:
Handle: RePEc:wpa:wuwpem:0508006

Note: Type of Document - pdf; prepared on windows; pages: 9. pdf for Windows document submitted via ftp
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Web page: http://129.3.20.41

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Related research
Keywords: deconvolution; density estimation; errors-in-variables; kernel; simulations;

Find related papers by JEL classification:
C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General
C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
C5 - Mathematical and Quantitative Methods - - Econometric Modeling
C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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References listed on IDEAS
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. Joel L. Horowitz & Marianthi Markatou, 1993. "Semiparametric Estimation Of Regression Models For Panel Data," Econometrics 9309001, EconWPA. [Downloadable!]
  2. Wand, M. P., 1998. "Finite sample performance of deconvolving density estimators," Statistics & Probability Letters, Elsevier, vol. 37(2), pages 131-139, February. [Downloadable!] (restricted)
  3. Horowitz, Joel L & Markatou, Marianthi, 1996. "Semiparametric Estimation of Regression Models for Panel Data," Review of Economic Studies, Blackwell Publishing, vol. 63(1), pages 145-68, January. [Downloadable!] (restricted)
  4. Laurent E. Calvet & Etienne Comon, 2000. "Behavioral Heterogeneity and The Income Effect," Harvard Institute of Economic Research Working Papers 1892, Harvard - Institute of Economic Research.
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This page was last updated on 2009-11-20.

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