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A class of count models and a new consistent test for the Poisson distribution. / Meintanis, S. G.; Nikitin, Ya Yu.

In: Journal of Statistical Planning and Inference, Vol. 138, No. 12, 01.12.2008, p. 3722-3732.

Research output: Contribution to journal › Article › peer-review

Harvard

Meintanis, SG & Nikitin, YY 2008, 'A class of count models and a new consistent test for the Poisson distribution', Journal of Statistical Planning and Inference, vol. 138, no. 12, pp. 3722-3732. https://doi.org/10.1016/j.jspi.2007.12.011

APA

Meintanis, S. G., & Nikitin, Y. Y. (2008). A class of count models and a new consistent test for the Poisson distribution. Journal of Statistical Planning and Inference, 138(12), 3722-3732. https://doi.org/10.1016/j.jspi.2007.12.011

Vancouver

Meintanis SG, Nikitin YY. A class of count models and a new consistent test for the Poisson distribution. Journal of Statistical Planning and Inference. 2008 Dec 1;138(12):3722-3732. https://doi.org/10.1016/j.jspi.2007.12.011

Author

Meintanis, S. G. ; Nikitin, Ya Yu. / A class of count models and a new consistent test for the Poisson distribution. In: Journal of Statistical Planning and Inference. 2008 ; Vol. 138, No. 12. pp. 3722-3732.

BibTeX

@article{6c4d5599713841048afa90e2533b8e8e,
title = "A class of count models and a new consistent test for the Poisson distribution",
abstract = "We define a class of count distributions which includes the Poisson as well as many alternative count models. Then the empirical probability generating function is utilized to construct a test for the Poisson distribution, which is consistent against this class of alternatives. The limit distribution of the test statistic is derived in case of a general underlying distribution, and efficiency considerations are addressed. A simulation study indicates that the new test is comparable in performance to more complicated omnibus tests.",
keywords = "Count distribution, Empirical probability generating function, Goodness-of-fit test, Stein's identity",
author = "Meintanis, {S. G.} and Nikitin, {Ya Yu}",
year = "2008",
month = dec,
day = "1",
doi = "10.1016/j.jspi.2007.12.011",
language = "English",
volume = "138",
pages = "3722--3732",
journal = "Journal of Statistical Planning and Inference",
issn = "0378-3758",
publisher = "Elsevier",
number = "12",

}

RIS

TY - JOUR

T1 - A class of count models and a new consistent test for the Poisson distribution

AU - Meintanis, S. G.

AU - Nikitin, Ya Yu

PY - 2008/12/1

Y1 - 2008/12/1

N2 - We define a class of count distributions which includes the Poisson as well as many alternative count models. Then the empirical probability generating function is utilized to construct a test for the Poisson distribution, which is consistent against this class of alternatives. The limit distribution of the test statistic is derived in case of a general underlying distribution, and efficiency considerations are addressed. A simulation study indicates that the new test is comparable in performance to more complicated omnibus tests.

AB - We define a class of count distributions which includes the Poisson as well as many alternative count models. Then the empirical probability generating function is utilized to construct a test for the Poisson distribution, which is consistent against this class of alternatives. The limit distribution of the test statistic is derived in case of a general underlying distribution, and efficiency considerations are addressed. A simulation study indicates that the new test is comparable in performance to more complicated omnibus tests.

KW - Count distribution

KW - Empirical probability generating function

KW - Goodness-of-fit test

KW - Stein's identity

UR - http://www.scopus.com/inward/record.url?scp=49649108842&partnerID=8YFLogxK

U2 - 10.1016/j.jspi.2007.12.011

DO - 10.1016/j.jspi.2007.12.011

M3 - Article

AN - SCOPUS:49649108842

VL - 138

SP - 3722

EP - 3732

JO - Journal of Statistical Planning and Inference

JF - Journal of Statistical Planning and Inference

SN - 0378-3758

IS - 12

ER -

ID: 47771321