Efficient computation of pattern statistics for many different input probabilities

Oregon Convention Center 

A Markov chain-based approach yields an efficient computation mechanism to compute a single distribution of a pattern statistic in a Markovian sequence. However, if distributions are needed for many values of input probabilities, the entire computation needs to be repeated. The method forwarded in this work avoids the need to redo recursive updates of probabilities. Instead, counts of data strings with various values of sufficient statistics are updated recursively. The final counts are then used to reconstruct probabilities for the many input probabilities, improving efficiency. In this talk, the methodology is laid out systematically.

Markovian data, parameter-free computation, recursive computation 

Section on Statistical Computing