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Multi-dimensional Contingency Tables
1990In chapter 5, log-linear models for three-dimensional tables were treated in great details. Hence we shall not for higher order tables go into details with the parameterizations of the models or with the exact expressions for test quantities and their distributions.
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1990
Consider a three-way contingency table {Xijk, i=1,...I, j=1,...,J, k=1,...,K}. As model for such data, it may be assumed that the x’s are observed values of random variables Xijk, i=1,...,I, j=1,...,J, k=1,...,K with a multinomial distribution $${X_{111}},...,{X_{IJK}} \sim M(n,{p_{111}},...,{p_{IJK}}).$$ (5.1)
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Consider a three-way contingency table {Xijk, i=1,...I, j=1,...,J, k=1,...,K}. As model for such data, it may be assumed that the x’s are observed values of random variables Xijk, i=1,...,I, j=1,...,J, k=1,...,K with a multinomial distribution $${X_{111}},...,{X_{IJK}} \sim M(n,{p_{111}},...,{p_{IJK}}).$$ (5.1)
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The AME 2020 atomic mass evaluation (II). Tables, graphs and references*
Chinese Physics C, 2021Meng Wang, Filip Kondev, Sarah Naimi
exaly
Solar cell efficiency tables (Version 60)
Progress in Photovoltaics: Research and Applications, 2022Martin A Green, Masahiro Yoshita
exaly
Synthesis of Corroles and Their Heteroanalogs
Chemical Reviews, 2017Rafał Orłowski, Dorota Gryko
exaly