Good-Turing frequency estimation without tears.

Gale, William A and Sampson, Geoffrey (1995) Good-Turing frequency estimation without tears. Journal of Quantitative Linguistics, 2 (3). pp. 217-237.

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Linguists and speech researchers who use statistical methods often need to estimate the frequency of some type of item in a population containing items of various types. A common approach is to divide the number of cases observed in a sample by the size of the sample; sometimes small positive quantities are added to divisor and dividend in order to avoid zero estimates for types missing from the sample. These approaches are obvious and simple, but they lack principled justification, and yield estimates that can be wildly inaccurate. I.J. Good and Alan Turing developed a family of theoretically well‐founded techniques appropriate to this domain. Some versions of the Good‐Turing approach are very demanding computationally, but we define a version, the Simple Good‐Turing estimator, which is straightforward to use. Tested on a variety of natural‐language‐related data sets, the Simple Good‐Turing estimator performs well, absolutely and relative both to the approaches just discussed and to other, more sophisticated techniques.

Item Type: Article
Additional Information: nominally 1995 but in fact 1996 (after the deadline for the last exercise).
Schools and Departments: School of Engineering and Informatics > Informatics
Depositing User: Geoffrey Richard Sampson
Date Deposited: 06 Feb 2012 19:30
Last Modified: 24 Sep 2019 13:56
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