NDLI: Hypothesis Tests on Mixture Model Components with Applications in Ecology and Agriculture

Content Provider	Springer Nature Link
Author	Xu, Ling Hanson, Timothy Bedrick, Edward J. Restrepo, Carla
Copyright Year	2010
Abstract	Multiple comparisons are widely used to compare gross features of distributions across populations. However, often a scientific hypothesis is more easily couched in terms of more focused null and alternative statistical hypotheses. For example, among distributions exhibiting clusters of continuous measurements across strata, are there clusters of measurements similar in terms of location, spread, or weight? We propose testing such hypotheses using a sequence of nested finite mixture models. Reasonable, data-driven priors are suggested based on estimates of the sample spreads and midpoints. Formal hypothesis testing is carried out through the computation of Bayes factors. The method is illustrated on Holling’s (Ecological Monographs 62:447–502, 1992) forest and prairie bird body mass data, and data on the time-to-abortion in dairy cows. Supplemental simulations are available online.
Starting Page	308
Ending Page	326
Page Count	19
File Format	PDF
ISSN	10857117
Journal	Journal of Agricultural, Biological, and Environmental Statistics
Volume Number	15
Issue Number	3
e-ISSN	15372693
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-03-20
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Finite mixture model Hierarchical mixture of experts Multiple comparisons Textural-discontinuity hypothesis Biostatistics Environmental Monitoring/Analysis Agriculture Statistics for Life Sciences, Medicine, Health Sciences
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty

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