The Annals of Statistics
- Ann. Statist.
- Volume 4, Number 4 (1976), 766-770.
Probabilities of Large Deviations for Empirical Measures
Abstract
Sanov's theorem on the asymptotic behavior of probabilities of large deviations for an empirical probability distribution is established under different conditions than previously given by Sanov, Hoadley and Stone. The new conditions are based on likelihood ratio approximations rather than on multinomial approximations. It is shown that these conditions are strictly more general than those of Stone.
Article information
Source
Ann. Statist., Volume 4, Number 4 (1976), 766-770.
Dates
First available in Project Euclid: 12 April 2007
Permanent link to this document
https://projecteuclid.org/euclid.aos/1176343548
Digital Object Identifier
doi:10.1214/aos/1176343548
Mathematical Reviews number (MathSciNet)
MR415836
Zentralblatt MATH identifier
0367.60025
JSTOR
links.jstor.org
Subjects
Primary: 60F10: Large deviations
Secondary: 62F20 62G20: Asymptotic properties
Keywords
Large deviations exact slope empirical probability measures likelihood ratio
Citation
Sievers, Gerald L. Probabilities of Large Deviations for Empirical Measures. Ann. Statist. 4 (1976), no. 4, 766--770. doi:10.1214/aos/1176343548. https://projecteuclid.org/euclid.aos/1176343548
