Electronic Journal of Statistics
- Electron. J. Statist.
- Volume 3 (2009), 1021-1038.
Empirical measures for incomplete data with applications
Methods are proposed to construct empirical measures when there are missing terms among the components of a random vector. Furthermore, Vapnik-Chevonenkis type exponential bounds are obtained on the uniform deviations of these estimators, from the true probabilities. These results can then be used to deal with classical problems such as statistical classification, via empirical risk minimization, when there are missing covariates among the data. Another application involves the uniform estimation of a distribution function.
Electron. J. Statist., Volume 3 (2009), 1021-1038.
First available in Project Euclid: 13 October 2009
Permanent link to this document
Digital Object Identifier
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Primary: 60G50: Sums of independent random variables; random walks 62G15: Tolerance and confidence regions
Secondary: 62H30: Classification and discrimination; cluster analysis [See also 68T10, 91C20]
Chenouri, Shojaeddin; Mojirsheibani, Majid; Montazeri, Zahra. Empirical measures for incomplete data with applications. Electron. J. Statist. 3 (2009), 1021--1038. doi:10.1214/09-EJS420. https://projecteuclid.org/euclid.ejs/1255440399