Smooth Tests for the Zero‐Inflated Poisson Distribution
In this article we construct three smooth goodness‐of‐fit tests for testing for the zero‐inflated Poisson (ZIP) distribution against general smooth alternatives in the sense of Neyman. We apply our tests to a data set previously claimed to be ZIP distributed, and show that the ZIP is not a good mode...
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| Veröffentlicht in: | Biometrics 2005-09, Vol.61 (3), p.808-815 |
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| container_title | Biometrics |
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| creator | Thas, Olivier Rayner, J. C. W. |
| description | In this article we construct three smooth goodness‐of‐fit tests for testing for the zero‐inflated Poisson (ZIP) distribution against general smooth alternatives in the sense of Neyman. We apply our tests to a data set previously claimed to be ZIP distributed, and show that the ZIP is not a good model to describe the data. At rejection of the null hypothesis of ZIP, the individual components of the test statistic, which are directly related to interpretable parameters in a smooth model, may be used to gain insight into an alternative distribution. |
| doi_str_mv | 10.1111/j.1541-0420.2005.00351.x |
| format | Article |
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C. W.</creatorcontrib><title>Smooth Tests for the Zero‐Inflated Poisson Distribution</title><title>Biometrics</title><addtitle>Biometrics</addtitle><description>In this article we construct three smooth goodness‐of‐fit tests for testing for the zero‐inflated Poisson (ZIP) distribution against general smooth alternatives in the sense of Neyman. We apply our tests to a data set previously claimed to be ZIP distributed, and show that the ZIP is not a good model to describe the data. At rejection of the null hypothesis of ZIP, the individual components of the test statistic, which are directly related to interpretable parameters in a smooth model, may be used to gain insight into an alternative distribution.</description><subject>Animals</subject><subject>Biometrics</subject><subject>biometry</subject><subject>Computer Simulation</subject><subject>data collection</subject><subject>Data Interpretation, Statistical</subject><subject>Estimation methods</subject><subject>Estimators</subject><subject>Fetal Movement - physiology</subject><subject>Generalized score test</subject><subject>Hypothesis testing</subject><subject>Mathematical independent variables</subject><subject>Mathematical moments</subject><subject>Maximum likelihood estimation</subject><subject>Neyman smooth test</subject><subject>Null hypothesis</subject><subject>Orthonormal polynomials</subject><subject>Parametric models</subject><subject>Poisson Distribution</subject><subject>Polynomials</subject><subject>Regression Analysis</subject><subject>Sheep - embryology</subject><subject>Statistics</subject><issn>0006-341X</issn><issn>1541-0420</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkc1u1DAUhS0EokPhDRBELNglXP_GWbCAAu1UU1qprQaxsZzEpkkzcbETMd31EfqMPEk9ZDRIrPDG1zrfuffqGKEEQ4bjeddmmDOcAiOQEQCeAVCOs_UjNNsJj9EMAERKGf62h56F0MZnwYE8RXtYYMqBkhkqzlfODVfJhQlDSKzzyXBlku_Gu9939_PednowdXLmmhBcn3xqwuCbchwa1z9HT6zugnmxvffR5ZfPFwdH6eL0cH7wYZFWLM9xmudWAtRFGUdWNidEc1bF2poauGG15aClLJkASXRpiKhtQUjBQHIprCzoPno79b3x7ucY11SrJlSm63Rv3BiUkJzxAnAE3_wDtm70fdxNEUwlFZjICMkJqrwLwRurbnyz0v5WYVCbbFWrNhGqTYRqk636k61aR-urbf-xXJn6r3EbZgTeT8CvpjO3_91YfZyfnsQq-l9O_jYMzu_8VBRcYIhyOsnxE8x6J2t_rUROc66WXw_V8ZKdLI7OhFpG_vXEW-2U_uGboC7PCWAOgFkuaUEfAEJbp-0</recordid><startdate>200509</startdate><enddate>200509</enddate><creator>Thas, Olivier</creator><creator>Rayner, J. 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W.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Smooth Tests for the Zero‐Inflated Poisson Distribution</atitle><jtitle>Biometrics</jtitle><addtitle>Biometrics</addtitle><date>2005-09</date><risdate>2005</risdate><volume>61</volume><issue>3</issue><spage>808</spage><epage>815</epage><pages>808-815</pages><issn>0006-341X</issn><eissn>1541-0420</eissn><coden>BIOMA5</coden><abstract>In this article we construct three smooth goodness‐of‐fit tests for testing for the zero‐inflated Poisson (ZIP) distribution against general smooth alternatives in the sense of Neyman. We apply our tests to a data set previously claimed to be ZIP distributed, and show that the ZIP is not a good model to describe the data. 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| ispartof | Biometrics, 2005-09, Vol.61 (3), p.808-815 |
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| source | MEDLINE; JSTOR Mathematics & Statistics; Access via Wiley Online Library; JSTOR Archive Collection A-Z Listing; Oxford University Press Journals All Titles (1996-Current) |
| subjects | Animals Biometrics biometry Computer Simulation data collection Data Interpretation, Statistical Estimation methods Estimators Fetal Movement - physiology Generalized score test Hypothesis testing Mathematical independent variables Mathematical moments Maximum likelihood estimation Neyman smooth test Null hypothesis Orthonormal polynomials Parametric models Poisson Distribution Polynomials Regression Analysis Sheep - embryology Statistics |
| title | Smooth Tests for the Zero‐Inflated Poisson Distribution |
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