Abstract
For data obtained by sampling from a mixture of several components whose concentration varies in the the course of observations, we construct an empirical Bayes classifier and consider its asymptotic properties.
Similar content being viewed by others
REFERENCES
L. Devroye and L. Györfi, Nonparametric Density Estimation. The L 1 View [Russian translation], Mir, Moscow (1988).
R. E. Maiboroda, “Estimates for distributions of components of mixtures with varying concentrations,” Ukr. Mat. Zh., 48, No. 4, 562–566 (1996).
O. V. Suhakova, “Asymptotics of a kernel estimator of a distribution density on the basis of observations of a mixture with varying concentrations,” Teor. Imov. Mat. Statist., Issue 59, 156–166 (1998).
V. V. Buldygin and Yu. V. Kozachenko, Metric Characteristics of Random Variables and Processes [in Russian], TViMS, Kiev (1998).
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Ivan'ko, Y.O., Maiboroda, R.E. Exponential Estimates for an Empirical Bayes Risk in Classification of a Mixture with Varying Concentrations. Ukrainian Mathematical Journal 54, 1722–1731 (2002). https://doi.org/10.1023/A:1023792522291
Issue Date:
DOI: https://doi.org/10.1023/A:1023792522291