A graphical approach for goodness-of-fit of Poisson model

Extensive work has been done on goodness-of-fit (GOF) tests for data assumed to have come from univariate continuous distributions; however, literature on GOF procedures for univariate discrete distributions is rather sparse in compariSon The Poisson distribution in particular has received much attention in the study of GOF tests due to its numerous applications as a model for observable phenomena. Hence, we survey existing GOF tests for Poissonity and present a useful guide to the most commonly used distribution-free GOF tests in practice. We then propose and investigate a graphical test of fit for the Poisson model that is based on a Poisson Q-Q plot, a squared correlation coefficient R2 test statistic, and a sampling distribution of the R2 test statistic simulated by parametric bootstrap. Similar methods exist for continuous distributions like the univariate normal and extreme-value distributions under regression tests of fit. Simulated examples as well as historically well-known Poisson data sets are then used to illustrate the proposed goodness-of-fit test for Poissonity.

Name thesis:degree_name

Master of Science (MS)

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Mathematical Sciences

Grantor dc:publisher

University of Nevada, Las Vegas

Year

2003

Author dc:creator

• Padilla, Davin P

Contributors dc:contributor

• Ashok K. Singh

Statement dc:rights

• IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

Language dc:language

English

Identifier

https://oasis.library.unlv.edu/rtds/1607

OAI identifier oai:identifier

oai:oasis.library.unlv.edu:rtds-2606