Kernel Estimation of probability density function: properties and parameters optimization

• Autorzy: Jerzman B. , Kiciński W.
• Języki publikacji: EN

Abstrakty

EN

The article deals with the kernel estimation of the probability density function. The main subject of the research is the optimization of parameters of the estimator. In the particular case, the research focused on the estimation of the univariate, unimodal data representative for the normal distribution.

Słowa kluczowe

EN

probability density function; kernel estimation

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2009
• Tom: Vol. 16, nr 1
• Strony: 85--105
• Opis fizyczny: Bibliogr. 9 poz.,tab., wykr.

Twórcy

autor

Jerzman B.

autor

Kiciński W.

• Naval Information Technology Group, Arciszewskiego 25, 81-103 Gdynia, Poland,

Bibliografia

• [1] B.W. Silverman: Density estimation for statistics and data analysis, Chapman and Hall, London, 1986.
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• [3] W. Zhang, L. Wenyin, K. Zhang: “Symbol recognition with Kernel Density Matching”. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 12, 2006, pp. 2020-2024.
• [4] T. Parag, A. Elgammal, A. Mittal: “A Framework for Feature Selection for Background Subtraction”. Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, 2006, pp. 1916-1923.
• [5] P. Kulczycki: Kernel estimators in system analysis, WNT, Warsaw, 2005. (in Polish).
• [6] S.J. Sheather: “Density Estimation”. Statistical Science, vol. 19, no. 4, 2004, pp. 588-597.
• [7] D.W. Scott: Multivariate Density Estimation. Theory, Practice and Visualization, Wiley, New York 1992.
• [8] C.R.: “Bandwidth selection: classical or plug-in?” The Annals of Statistics, vol. 27, no. 2, 1999, pp. 415-438.
• [9] P. Hall, S.J. Sheather, M.C. Jones, J.S. Marron: “On optimal data-based bandwidth selection in kernel density estimation”, Biometrika, vol. 78, no. 2, 1991, pp. 263-269.