In information theory, given an unknown stationary source π with alphabet A and a sample w from π, the Krichevsky–Trofimov (KT) estimator produces an estimate πi(w) of the probabilities of each symbol i ∈ A. This estimator is optimal in the sense that it minimizes the worst-case regret asymptotically.
For a binary alphabet and a string w with m zeroes and n ones, the KT estimator P(m, n) can be defined recursively:
- Krichevsky, R. E. and Trofimov V. K. (1981), "The Performance of Universal Encoding", IEEE Trans. Information Theory, Vol. IT-27, No. 2, pp. 199–207.
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