Antos, A and Kontoyiannis, I (2001) *Convergence properties of functional estimates for discrete distributions.* Random Structures and Algorithms, 19. pp. 163-193. ISSN 1042-9832

## Abstract

Suppose P is an arbitrary discrete distribution on a countable alphabet script X. Given an i.i.d. sample (X1 , . . . , Xn) drawn from P, we consider the problem of estimating the entropy H(P) or some other functional F = F(P) of the unknown distribution P. We show that, for additive functionals satisfying mild conditions (including the cases of the mean, the entropy, and mutual information), the plug-in estimates of F are universally consistent. We also prove that, without further assumptions, no rate-of-convergence results can be obtained for any sequence of estimators. In the case of entropy estimation, under a variety of different assumptions, we get rate-of-convergence results for the plug-in estimate and for a nonparametric estimator based on match-lengths. The behavior of the variance and the expected error of the plug-in estimate is shown to be in sharp contrast to the finite-alphabet case. A number of other important examples of functionals are also treated in some detail. © 2001 John Wiley & Suns, Inc.

Item Type: | Article |
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Subjects: | UNSPECIFIED |

Divisions: | Div F > Signal Processing and Communications |

Depositing User: | Unnamed user with email sms67@cam.ac.uk |

Date Deposited: | 08 Jan 2018 20:11 |

Last Modified: | 22 Oct 2019 05:57 |

DOI: | 10.1002/rsa.10019 |