Minimal logic

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 π_i(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 can be defined recursively as:

${\begin{array}{lcl}P(0,0)&=&1,\\[6pt]P(m,n+1)&=&P(m,n){\dfrac {n+1/2}{m+n+1}},\\[12pt]P(m+1,n)&=&P(m,n){\dfrac {m+1/2}{m+n+1}}.\end{array}}$

See also

• Rule of succession

References

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