QUASI-POISSON VS. NEGATIVE BINOMIAL REGRESSION: HOW SHOULD WE MODEL OVERDISPERSED COUNT DATA?

Jay M. Ver Hoef; Peter L. Boveng

doi:10.1890/07-0043.1

journal article Nov 01, 2007

QUASI-POISSON VS. NEGATIVE BINOMIAL REGRESSION: HOW SHOULD WE MODEL OVERDISPERSED COUNT DATA?

Jay M. Ver Hoef

Peter L. Boveng

Ecology Vol. 88 No. 11 pp. 2766-2772 · Wiley

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References

22

[1]

10.1093/biostatistics/1.4.453

[2]

10.1111/j.1748-7692.2003.tb01096.x

[3]

10.2307/3800260

[4]

10.2307/2289002

[5]

10.1111/j.1748-7692.1999.tb00815.x

[6]

10.1037/0033-2909.118.3.392

[7]

10.1093/biomet/77.1.55

[8]

10.1002/bimj.200410102

[9]

Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing

Diane Lambert

Technometrics 10.2307/1269547

[10]

Lee Y. Applied Statistics (2000)

[11]

10.1016/j.aap.2004.02.004

[12]

Mathews E. A. Marine Mammal Science (2006) 10.1111/j.1748-7692.2006.00011.x

[13]

10.1111/j.1365-2656.2005.00940.x

[14]

10.1016/j.ecolmodel.2006.05.025

[15]

Modeling by shortest data description

J. Rissanen

Automatica 10.1016/0005-1098(78)90005-5

[16]

Estimating the Dimension of a Model

Gideon Schwarz

The Annals of Statistics 10.1214/aos/1176344136

[17]

10.1079/ber2005401

[18]

10.1111/j.1748-7692.2003.tb01113.x

[19]

Terceiro M. Fishery Bulletin (2003)

[20]

10.1023/a:1023626308538

[21]

Wedderburn R. W. M. Biometrika (1974)

[22]

10.2307/2265753

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Details

Published: Nov 01, 2007
Vol/Issue: 88(11)
Pages: 2766-2772
License: View

Authors

J

Jay M. Ver Hoef

National Marine Mammal Laboratory Alaska Fisheries Science Center National Marine Fisheries Service NOAA 7600 Sand Point Way NE Seattle Washington 98115 U.S.A

P

Peter L. Boveng

National Marine Mammal Laboratory Alaska Fisheries Science Center National Marine Fisheries Service NOAA 7600 Sand Point Way NE Seattle Washington 98115 U.S.A

Cite This Article

Jay M. Ver Hoef, Peter L. Boveng (2007). QUASI-POISSON VS. NEGATIVE BINOMIAL REGRESSION: HOW SHOULD WE MODEL OVERDISPERSED COUNT DATA?. Ecology, 88(11), 2766-2772. https://doi.org/10.1890/07-0043.1

QUASI-POISSON VS. NEGATIVE BINOMIAL REGRESSION: HOW SHOULD WE MODEL OVERDISPERSED COUNT DATA?

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