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We develop the theory and their application for statistical analysis. Let B 0, 1 ), xN BN (x1 , ..., xN ) be a stationary ergodic random binary (training) string (text, SET) distributed as P0 P . Arbitrary UC (see 15 ) maps source strings xN BN into compressed binary strings xN of c approximate length xN log P (xN )) LN thus generating the approximate Loglikelihood c of source xN the main inference tool about P . Consider a query binary SET yM distributed as P1 an.

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