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Bayesian analysis of agricultural field experiments. (With discussion). (English) Zbl 0951.62091
Summary: The paper describes Bayesian analysis for agricultural field experiments, a topic that has received very little previous attention, despite a vast frequentist literature. Adoption of the Bayesian paradigm simplifies the interpretation of the results, especially in ranking and selection. Also, complex formulations can be analysed with comparative ease, by using Markov chain Monte Carlo methods. A key ingredient in the approach is the need for spatial representations of the unobserved fertility patterns. This is discussed in detail. Problems caused by outliers and by jumps in fertility are tackled via hierarchical-\(t\) formulations that may find use in other contexts. The paper includes three analyses of variety trials for yield and one example involving binary data; none is entirely straight-forward. Some numerical comparisons with frequentist analyses are made.

MSC:
62P10 Applications of statistics to biology and medical sciences; meta analysis
62F15 Bayesian inference
62P12 Applications of statistics to environmental and related topics
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