On Logarithmically Asymptotically Optimal Hypothesis Testing for Arbitrarily Varying Sources with Side Information

Ahlswede, Rudolf; Aloyan, Ella; Haroutunian, Evgueni A.

doi:10.1007/11889342_32

Cited by 6 publications

(1 citation statement)

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“…So the HT problem of [8] targets the identification of the distribution family of observations instead of predicting the generic distribution of a DMS without option to reject both the hypothetical laws about it. Furthermore, the work [1] considered the problem by Fu and Shen [8] in case of decision making with known to statistician states of the source. This side information simplifies the decision making.…”

Section: Introductionmentioning

confidence: 99%

Multiple hypothesis testing for arbitrarily varying sources

Grigoryan

Harutyunyan

2015

Communications in Information and Systems

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Highly unstable environments can be modeled by arbitrarily varying (information) sources (AVS). We conduct a study of multiple hypothesis testing (HT) for those sources within two approaches existing in an information-theoretic area of statistical analysis. First we characterize the attainable exponent trade-offs for all kind of error probabilities and indicate the corresponding decision schemes or testing strategies. Then we treat the same problem from an optimality achieving perspectives.Moreover, Chernoff bounds for both the binary and M -ary HT are specified via indication of a Sanov theorem for AVS's. Additional geometric interpretations help to digest the structure of HT in derived solutions.

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Section: Introductionmentioning

confidence: 99%