Multiple Hypothesis Testing by Finite Memory Algorithms
In recent years, a theory has been emerging concerning the statistical power of small computers. In the present paper it is proven that in the sense peculiar to this literature, small computers (mathematically equivalent to finite automata) can in general be designed to solve multiple simple hypothesis testing problems. In many cases, only one state for each hypothesis is needed. In a more conventional sense, we reveal the construction of finite automata which implement sequential decision procedures having the capacity to distinguish between any given finite set of probabilities with any desired accuracy. Finally, some results on the ability of finite automata to track time--changing hypotheses are outlined.
Permanent link to this document: http://projecteuclid.org/euclid.aos/1176342666
Digital Object Identifier: doi:10.1214/aos/1176342666
Mathematical Reviews number (MathSciNet): MR363738
Zentralblatt MATH identifier: 0277.62019