Models for strawberry inflorescence data

Cole, D.J. and Morgan, B.J.T. and Ridout, M.S. (2005) Models for strawberry inflorescence data. Journal of Agricultural, Biological, and Environmental Statistics, 10 (4). pp. 411-423. ISSN 1085-7117. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1198/108571105X80761

Abstract

The flowers of strawberry plants grow on very variable branched structures called inflorescences, in which each branch gives rise to 0, 1, or 2 offspring branches. We extend previous modeling of the number of strawberry flowers at each individual level in the inflorescence structure conditional on the number of strawberry flowers at the previous level. We consider a range of logistic regression models, including models that incorporate inflorescence effects and random effects. The models can be used to summarize the overall structure of any particular variety and to indicate the main differences between varieties. For the data of the article, we show that models based on convolutions of correlated Bernoulli random variables outperform binomial regression models.

Item Type: Article
Uncontrolled keywords: categorical data; correlated Bernoulli; logistic regression; mixed models; multinomial; nominal logistic regression; random effects CONTINGENCY-TABLES; MIXED MODELS
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Judith Broom
Date Deposited: 05 Sep 2008 21:44
Last Modified: 14 Jan 2010 14:40
Resource URI: http://kar.kent.ac.uk/id/eprint/10500 (The current URI for this page, for reference purposes)
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