Probability Value Library

Abstract:

Hidden Markov models (HMMs) and other time series models assign
probabilities to long sequences of events. Avoiding underflow is
arguably the central difficulty in calculating the probability of long
event sequences. This technical report presents an elegant and
efficient C library for representing and manipulating probability
values without underflow. Use of the library results in simpler code
whose execution time compares favorably with traditional numerical
methods. Our abstraction leads to a natural extension of the IEEE
floating point standard, to better support statistical computation.