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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
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Abstract |
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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. |
Keywords
method of moments estimation, maximum likelihood
estimation, bias, mean squared error
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Mathematical Subject Classification 2010
Primary: 62F10
Secondary: 62F86, 62P12
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Milestones
Received: 24 July 2013
Revised: 6 December 2013
Accepted: 3 January 2014
Published: 20 October 2014
Communicated by Sat N. Gupta
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Authors |
| Sadie Beckett | |
| University of Louisiana at
Lafayette 104 E University Avenue Lafayette, LA 70504 United States |
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| Joshua Jee | |
| Louisiana College Pineville, LA 71360 United States |
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| Thapelo Ncube | |
| University of West Florida 11000 University Parkway Pensacola, FL 32514 United States |
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| Sophia Pompilus | |
| Georgetown University 3700 O St NW Washington, DC 20057 United States |
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| Quintel Washington | |
| Southern University New
Orleans 6400 Press Drive New Orleans, LA 70126 United States |
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| Anshuman Singh | |
| University of Louisiana at
Lafayette 104 E University Avenue Lafayette, LA 70504 United States |
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| Nabendu Pal | |
| Department of Mathematics University of Louisiana at Lafayette PO Box 41010 Lafayette, LA 70504 United States |
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