MODELING INSECT-EGG DATA WITH EXCESS ZEROS USING ZERO-INFLATED REGRESSION MODELS

Yeşilova A., Kaydan M. B., KAYA Y.

HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS, vol.39, no.2, pp.273-282, 2010 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 39 Issue: 2
  • Publication Date: 2010
  • Journal Name: HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.273-282
  • Van Yüzüncü Yıl University Affiliated: Yes

Abstract

As zero-inflated observations occur very often in studies on plant protection, models taking into account zero-inflated observations are frequently required. Especially, zero-inflated observations occur in large numbers for insects whose post-oviposition period lasts long, or that generally lay their eggs during the first clays of the oviposition period. For the data used in this study, 1114 (43.84%) of the 2541 observations were zero. In the selection of an appropriate regression model, zero-inflated negative binomial regression was chosen as the best model. In all regression models, the day of laying and the three different hosts were seen to have a significant effect on daily egg numbers (p < 0.01).