Vol. 7, No. 6, 2014

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Zero-inflated Poisson (ZIP) distribution: parameter estimation and applications to model data from natural calamities

Sadie Beckett, Joshua Jee, Thapelo Ncube, Sophia Pompilus, Quintel Washington, Anshuman Singh and Nabendu Pal

Vol. 7 (2014), No. 6, 751–767

This work deals with estimation of parameters of a zero-inflated Poisson (ZIP) distribution as well as using it to model some natural calamities’ data. First, we compare the maximum likelihood estimators (MLEs) and the method of moments estimators (MMEs) in terms of standardized bias (SBias) and standardized mean squared error (SMSE). We then proceed to show how datasets from some recent natural disasters can be modeled by the ZIP distribution.

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method of moments estimation, maximum likelihood estimation, bias, mean squared error
Mathematical Subject Classification 2010
Primary: 62F10
Secondary: 62F86, 62P12
Received: 24 July 2013
Revised: 6 December 2013
Accepted: 3 January 2014
Published: 20 October 2014

Communicated by Sat N. Gupta
Sadie Beckett
University of Louisiana at Lafayette
104 E University Avenue
Lafayette, LA 70504
United States
Joshua Jee
Louisiana College
Pineville, LA 71360
United States
Thapelo Ncube
University of West Florida
11000 University Parkway
Pensacola, FL 32514
United States
Sophia Pompilus
Georgetown University
3700 O St NW
Washington, DC 20057
United States
Quintel Washington
Southern University New Orleans
6400 Press Drive
New Orleans, LA 70126
United States
Anshuman Singh
University of Louisiana at Lafayette
104 E University Avenue
Lafayette, LA 70504
United States
Nabendu Pal
Department of Mathematics
University of Louisiana at Lafayette
PO Box 41010
Lafayette, LA 70504
United States