Athanasios C. Rakitzis , Philippe Castagliola , Petros E. Maravelakis
{"title":"双参数广义膨胀泊松分布:性质与应用","authors":"Athanasios C. Rakitzis , Philippe Castagliola , Petros E. Maravelakis","doi":"10.1016/j.stamet.2015.10.002","DOIUrl":null,"url":null,"abstract":"<div><p>In this work, we propose and study a two-parameter modification of the ordinary Poisson distribution that is suitable for the modeling of non-typical count data. This model can be viewed as an extension of the zero-inflated Poisson distribution. We derive the proposed model as a special case of a general one and focus our study on it. The theoretical properties for each model are given, while estimation methods for the two-parameter model are discussed as well. Three practical examples illustrate its usefulness. The results show that the proposed model is very flexible in the modeling of various types of count data.</p></div>","PeriodicalId":48877,"journal":{"name":"Statistical Methodology","volume":"29 ","pages":"Pages 32-50"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.stamet.2015.10.002","citationCount":"9","resultStr":"{\"title\":\"A two-parameter general inflated Poisson distribution: Properties and applications\",\"authors\":\"Athanasios C. Rakitzis , Philippe Castagliola , Petros E. Maravelakis\",\"doi\":\"10.1016/j.stamet.2015.10.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this work, we propose and study a two-parameter modification of the ordinary Poisson distribution that is suitable for the modeling of non-typical count data. This model can be viewed as an extension of the zero-inflated Poisson distribution. We derive the proposed model as a special case of a general one and focus our study on it. The theoretical properties for each model are given, while estimation methods for the two-parameter model are discussed as well. Three practical examples illustrate its usefulness. The results show that the proposed model is very flexible in the modeling of various types of count data.</p></div>\",\"PeriodicalId\":48877,\"journal\":{\"name\":\"Statistical Methodology\",\"volume\":\"29 \",\"pages\":\"Pages 32-50\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.stamet.2015.10.002\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistical Methodology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S157231271500074X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistical Methodology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S157231271500074X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q","JCRName":"Mathematics","Score":null,"Total":0}
A two-parameter general inflated Poisson distribution: Properties and applications
In this work, we propose and study a two-parameter modification of the ordinary Poisson distribution that is suitable for the modeling of non-typical count data. This model can be viewed as an extension of the zero-inflated Poisson distribution. We derive the proposed model as a special case of a general one and focus our study on it. The theoretical properties for each model are given, while estimation methods for the two-parameter model are discussed as well. Three practical examples illustrate its usefulness. The results show that the proposed model is very flexible in the modeling of various types of count data.
期刊介绍:
Statistical Methodology aims to publish articles of high quality reflecting the varied facets of contemporary statistical theory as well as of significant applications. In addition to helping to stimulate research, the journal intends to bring about interactions among statisticians and scientists in other disciplines broadly interested in statistical methodology. The journal focuses on traditional areas such as statistical inference, multivariate analysis, design of experiments, sampling theory, regression analysis, re-sampling methods, time series, nonparametric statistics, etc., and also gives special emphasis to established as well as emerging applied areas.