The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Estimating the Number of Classes via Sample Coverage
Abstract
Assume that a random sample is drawn from a population with unknown number of classes and possibly unequal class probabilities. A nonparametric estimation technique is proposed to estimate the number of classes using the idea of sample coverage, which is defined as the sum of the cell probabilities of the observed classes. Since expected sample coverage can be well estimated, we were motivated to find its role in the estimation of the number of classes. This work generalizes the result of Esty to a nonparametric approach and extends Darroch and Ratcliff to incorporate the heterogeneity of the class probabilities. The coefficient of variation of the class sizes is shown to play an important role in the recommended estimation procedures. The performance of the proposed estimators is investigated by means of Monte Carlo simulations.
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Cites
Nonparametric estimation of the number of classes in a population
Chao, A. (1984) · Scandinavian Journal of Statistics · Cited by 4,265
Self-citationFisher, R. A., Corbet, A. S., & Williams, C. B. (1943) · The Journal of Animal Ecology · doi:10.2307/1411 · Cited by 3,487
THE POPULATION FREQUENCIES OF SPECIES AND THE ESTIMATION OF POPULATION PARAMETERS
GOOD, I. J. (1953) · Biometrika · doi:10.1093/biomet/40.3-4.237 · Cited by 3,437
Estimating the Population Size for Capture-Recapture Data with Unequal Catchability
Chao, A. (1987) · Biometrics · doi:10.2307/2531532 · Cited by 2,450
Self-citationScandinavian Journal of Statistics
(2010) · Scandinavian Journal of Statistics · doi:10.1111/(issn)1467-9469 · Cited by 976
Estimating the number of unseen species: How many words did Shakespeare know?
EFRON, B., & THISTED, R. (1976) · Biometrika · doi:10.1093/biomet/63.3.435 · Cited by 439
THE NUMBER OF NEW SPECIES, AND THE INCREASE IN POPULATION COVERAGE, WHEN A SAMPLE IS INCREASED
GOOD, I. J., & TOULMIN, G. H. (1956) · Biometrika · doi:10.1093/biomet/43.1-2.45 · Cited by 416
Did Shakespeare Write a Newly-Discovered Poem?
Thisted, R. A., & Efron, B. (1987) · Biometrika · doi:10.1093/biomet/74.3.445 · Cited by 175
Did Shakespeare Write a Newly-Discovered Poem?
Thisted, R. A., & Efron, B. (1987) · Biometrika · doi:10.2307/2336684 · Cited by 105
The Efficiency of Good's Nonparametric Coverage Estimator
Esty, W. W. (1986) · The Annals of Statistics · doi:10.1214/aos/1176350066 · Cited by 100
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Colwell, R. K., Chao, A., Gotelli, N. J., Lin, S.-Y., Mao, C. X., Chazdon, R. L., & Longino, J. T. (2012) · Journal of Plant Ecology · doi:10.1093/jpe/rtr044 · Cited by 1,921
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Metadata
- Authors
- Chao, A., & Lee, S.-M.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1992-03
- Volume
- 87
- Issue
- 417
- Pages
- 210-217
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2114413252
- Cited by
- 1,455
- References
- 10
- FWCI
- 3.67
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
