Testing for an excessive number of zeros in time series of bounded counts
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Hee-Young | - |
dc.contributor.author | Weiss, Christian H. | - |
dc.contributor.author | Moeller, Tobias A. | - |
dc.date.accessioned | 2021-09-02T02:20:05Z | - |
dc.date.available | 2021-09-02T02:20:05Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2018-12 | - |
dc.identifier.issn | 1618-2510 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/71274 | - |
dc.description.abstract | For the modeling of bounded counts, the binomial distribution is a common choice. In applications, however, one often observes an excessive number of zeros and extra-binomial variation, which cannot be explained by a binomial distribution. We propose statistics to evaluate the number of zeros and the dispersion with respect to a binomial model, which is based on the sample binomial index of dispersion and the sample binomial zero index. We apply this index to autocorrelated counts generated by a binomial autoregressive process of order one, which also includes the special case of independent and identically (i.i.d.) bounded counts. The limiting null distributions of the proposed test statistics are derived. A Monte-Carlo study evaluates their size and power under various alternatives. Finally, we present two real-data applications as well as the derivation of effective sample sizes to illustrate the proposed methodology. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER HEIDELBERG | - |
dc.subject | MODELS | - |
dc.title | Testing for an excessive number of zeros in time series of bounded counts | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Hee-Young | - |
dc.identifier.doi | 10.1007/s10260-018-00431-z | - |
dc.identifier.scopusid | 2-s2.0-85049576355 | - |
dc.identifier.wosid | 000452527500014 | - |
dc.identifier.bibliographicCitation | STATISTICAL METHODS AND APPLICATIONS, v.27, no.4, pp.689 - 714 | - |
dc.relation.isPartOf | STATISTICAL METHODS AND APPLICATIONS | - |
dc.citation.title | STATISTICAL METHODS AND APPLICATIONS | - |
dc.citation.volume | 27 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 689 | - |
dc.citation.endPage | 714 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordPlus | MODELS | - |
dc.subject.keywordAuthor | Binomial AR(1) model | - |
dc.subject.keywordAuthor | Binomial index of dispersion | - |
dc.subject.keywordAuthor | Binomial zero index | - |
dc.subject.keywordAuthor | Extra-binomial dispersion | - |
dc.subject.keywordAuthor | Extra-binomial zeros | - |
dc.subject.keywordAuthor | Adjusted sample size | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.