Journal article
Estimating a probability mass function with unknown labels
- Abstract:
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In the context of a species sampling problem, we discuss a nonparametric maximum likelihood estimator for the underlying probability mass function. The estimator is known in the computer science literature as the high profile estimator. We prove strong consistency and derive the rates of convergence, for an extended model version of the estimator. We also study a sieved estimator for which similar consistency results are derived. Numerical computation of the sieved estimator is of great inter...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Version of record, pdf, 237.8KB)
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- Publisher copy:
- 10.1214/17-AOS1542
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Authors
Funding
Bibliographic Details
- Publisher:
- Institute of Mathematical Statistics Publisher's website
- Journal:
- Annals of Statistics Journal website
- Volume:
- 45
- Issue:
- 6
- Pages:
- 2708-2735
- Publication date:
- 2017-12-15
- Acceptance date:
- 2016-05-23
- DOI:
- EISSN:
-
2168-8966
- ISSN:
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0090-5364
- Source identifiers:
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441614
Item Description
- Keywords:
- Pubs id:
-
pubs:441614
- UUID:
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uuid:6b36f895-96b3-42e7-8fcf-ebe9a296eca4
- Local pid:
- pubs:441614
- Deposit date:
- 2018-11-06
Terms of use
- Copyright holder:
- Institute of Mathematical Statistics
- Copyright date:
- 2017
- Notes:
- © Institute of Mathematical Statistics, 2017. This is the publisher's version of the article which is available online from Oxford University Press at: https://projecteuclid.org/euclid.aos/1513328588
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