Some remarks on Bayesian multiple hypothesis testing
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Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Hacettepe Univ, Fac Sci
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
We consider Bayesian multiple hypothesis problem with independent and identically distributed observations. The classical, Sanov's theorem-based, analysis of the error probability allows one to characterize the best achievable error exponent. However, this analysis does not generalize to the case where the true distributions of the hypothesis are not exact or partially known via some nominal distributions. This problem has practical significance, because the nominal distributions may be quantized versions of the true distributions in a hardware implementation, or they may be estimates of the true distributions obtained from labeled training sequences as in statistical classification. In this paper, we develop a type-based analysis to investigate Bayesian multiple hypothesis testing problem. Our analysis allows one to explicitly calculate the error exponent of a given type and extends the classical analysis. As a generalization of the proposed method, we derive a robust test and obtain its error exponent for the case where the hypothesis distributions are not known but there exist nominal distribution that are close to true distributions in variational distance.
Açıklama
Anahtar Kelimeler
Bayesian hypothesis testing, statistical classification, robust hypothesis testing, Chernoff information, method of types
Kaynak
Hacettepe Journal of Mathematics and Statistics
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
51
Sayı
1
