Using Zero-Inflated Generalized Poisson Regression in Modelling of Count Data
| dc.authorscopusid | 57193951641 | |
| dc.authorscopusid | 22036852300 | |
| dc.authorscopusid | 57193953008 | |
| dc.contributor.author | Soygüder, S. | |
| dc.contributor.author | Yeşilova, A. | |
| dc.contributor.author | Bora, Y. | |
| dc.date.accessioned | 2025-05-10T17:01:06Z | |
| dc.date.available | 2025-05-10T17:01:06Z | |
| dc.date.issued | 2017 | |
| dc.department | T.C. Van Yüzüncü Yıl Üniversitesi | en_US |
| dc.department-temp | Soygüder S., Yüzüncü Yıl Üniversitesi, Ziraat Fakültesi, Zootekni Bölümü, Van, Turkey; Yeşilova A., Yüzüncü Yıl Üniversitesi, Ziraat Fakültesi, Zootekni Bölümü, Van, Turkey; Bora Y., Yüzüncü Yıl Üniversitesi, Ziraat Fakültesi, Zootekni Bölümü, Van, Turkey | en_US |
| dc.description.abstract | In this study zero-inflated generalized Poisson regression was applied to the modelling of mite numbers data based on count. The subjects of the zero-inflated generalized Poisson regression are three parameters as mean, overdispersion and zero-inflated dispersion. The overdispersion and zero-inflated dispersion levels range was obtained to be quite high. However, it was found that zero-inflated data and overdispersion had an important effect on mite counts (p < 0.01). It was obtained that 36% (130 observations) of the total numbers of mite had zero values. The effects of all independent variables were found to be statistically significant on mite counts (p < 0.05). The results showed that the differences among regions and varieties regarding the mite counts were statistically significant (p < 0.01). © 2017, Centenary University. All rights reserved. | en_US |
| dc.identifier.doi | 10.29133/yyutbd.285706 | |
| dc.identifier.endpage | 117 | en_US |
| dc.identifier.issn | 1308-7576 | |
| dc.identifier.issue | 1 | en_US |
| dc.identifier.scopus | 2-s2.0-85017664973 | |
| dc.identifier.scopusquality | Q3 | |
| dc.identifier.startpage | 109 | en_US |
| dc.identifier.uri | https://doi.org/10.29133/yyutbd.285706 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14720/5047 | |
| dc.identifier.volume | 27 | en_US |
| dc.identifier.wosquality | N/A | |
| dc.language.iso | tr | en_US |
| dc.publisher | Centenary University | en_US |
| dc.relation.ispartof | Yuzuncu Yil University Journal of Agricultural Sciences | en_US |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | Mite Counts | en_US |
| dc.subject | Overdispersion | en_US |
| dc.subject | Zero-Inflated Data | en_US |
| dc.subject | Zero-Inflated Poisson Regression | en_US |
| dc.title | Using Zero-Inflated Generalized Poisson Regression in Modelling of Count Data | en_US |
| dc.type | Article | en_US |