A Better Good-Turing Estimator for Sequence Probabilities

Details A Better Good-Turing Estimator for Sequence Probabilities A Better Good-Turing Estimator for Sequence Probabilities

2007-04-11

arxiv.org/abs/0704.1455v2

Computer Science

Information Theory

ISIT 2007, to appear

Scientific paper

We consider the problem of estimating the probability of an observed string drawn i.i.d. from an unknown distribution. The key feature of our study is that the length of the observed string is assumed to be of the same order as the size of the underlying alphabet. In this setting, many letters are unseen and the empirical distribution tends to overestimate the probability of the observed letters. To overcome this problem, the traditional approach to probability estimation is to use the classical Good-Turing estimator. We introduce a natural scaling model and use it to show that the Good-Turing sequence probability estimator is not consistent. We then introduce a novel sequence probability estimator that is indeed consistent under the natural scaling model.

Affiliated with

Also associated with

No associations

Rating

A Better Good-Turing Estimator for Sequence Probabilities does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Better Good-Turing Estimator for Sequence Probabilities, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Better Good-Turing Estimator for Sequence Probabilities will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-673411