On some results of C. Radhakrishna Rao applicable to the analysis of multi-environment variety trials

DOI10.1080/15598608.2007.10411845zbMath1427.62128OpenAlexW2045208830MaRDI QIDQ2324038

Tadeusz Caliński

Publication date: 13 September 2019

Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/15598608.2007.10411845

zbMATH Keywords

series of experimentsgeneral mixed effects modelgeneralized lattice designvariance-covariance components estimation

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10) Statistical block designs (62K10) Analysis of variance and covariance (ANOVA) (62J10)

Cites Work

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• Representations of best linear unbiased estimators in the Gauss-Markoff model with a singular dispersion matrix
• Linear models. Least squares and alternatives
• Analyzing Variety by Environment Data Using Multiplicative Mixed Models and Adjustments for Spatial Field Trend
• Randomization and the Analysis of Variance
• A new class of resolvable incomplete block designs
• Average Information REML: An Efficient Algorithm for Variance Parameter Estimation in Linear Mixed Models
• Applications: The Analysis of Crop Variety Evaluation Data in Australia
• Mixed Models
• REML Estimation of Multiplicative Effects in Multienvironment Variety Trails
• Estimation of variance and covariance components—MINQUE theory
• Estimation of Variance and Covariance Components in Linear Models
• Analyzing Multi‐environment Variety Trials Using Randomization‐Derived Mixed Models
• The analysis of randomized experiments with orthogonal block structure. I. Block structure and the null analysis of variance
• General Methods of Analysis for Incomplete Block Designs
• The interpretation of negative components of variance

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