Model Selection and Validation for Yield Trials with Interaction

Gauch, H G (1988) Model Selection and Validation for Yield Trials with Interaction. Biometrics, 44 (3). pp. 705-715.

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The additive main effects and multiplicative interaction (AMMI) model first applies the additive analysis of variance (ANOVA) model to two-way data, and then applies the multiplicative principal components analysis (PCA) model to the residual from the additive model, that is, to the interaction. AMMI analysis of yield trial data is a useful extension of the more familiar AN OVA, PCA, and linear regression procedures, particularly given a large genotype-by-environment interaction. Model selection and validation are considered from both predictive and postdictive perspectives, using data splitting and F-tests, respectively. A New York soybean yield trial serves as an example.

Item Type: Article
Uncontrolled Keywords: AMMI: Analysis of variance: Biplot; Interaction: Model sequence: Postdiction: PredicĀ­ tion: Principal components analysis; Soyhean: Validation
Author Affiliation: Cornell University,Ithaca, New York,USA
Subjects: Crop Improvement
Divisions: Other Crops
Depositing User: Mr. SanatKumar Behera
Date Deposited: 04 Jan 2012 04:05
Last Modified: 04 Jan 2012 04:06
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