On the Choice of Smoothing Parameters for Parzen Estimators of Probability Density Functions

IEEE Transactions on Computers

Volumn C-25, Issue 11, 1976, Pages 1175-1179

  Duin, Robert P W ^a  

^a DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

Data analysis; multidimensional probability density function; multimodal probability density function; Parzen estimators; pattern recognition; smoothing

Indexed keywords

DATA PROCESSING;

EID: 0017017305     PISSN: 00189340     EISSN: None     Source Type: Journal    
DOI: 10.1109/TC.1976.1674577     Document Type: Article

References (8)

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3. D. O. Loftsgaarden and C. D. Quesenberry, “A nonparametric estimate of a multivariate density function,” Ann. Math. Statist., vol. 36, pp. 1049-1051, 1965.
4. V. K. Murthy, “Nonparametric estimation of multivariate densities with applications,” in Multivariate Analysis, P. R Krishnaiah, Ed. New York: Academic, 1966, pp. 43–48.
5. E. Parzen, “On the estimation of a probability density function and the mode.” Ann. Math. Statist., vol. 33, pp. 1065–1076, 1962.
6. E. A. Patrick and F. P. Fischer, “Nonparametric feature selection,” IEEE Trans. Inform. Theory, vol. IT-15, pp. 577–584, Sept. 1969.
7. D. F. Specht, “Generation of polynomical discriminant functions for pattern recognition,” IEEE Trans. Electron. Comput., vol.EC-16. pp. 308–319, Apr. 1967.
8. R. P. W. Duin, “A criterion for the smoothing parameter for Parzen estimators of probability density functions, Pattern Recognition Group, Dep. Appl. Phys., Delft Univ. Technol., Delft, The Netherlands, Internal Rep., Sept. 1975.