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Lindsey presents a complete range of material on this subject which can be immediately used with the major statistical packages. The important distinctions between independent and dependent events - frequencies and counts - structures the book. Many of the important areas of modern statistics from generalized linear models to survival analysis are demonstrated to be special cases of categorical data analysis.
Multivariate analysis. --- Multivariate distributions --- Multivariate statistical analysis --- Statistical analysis, Multivariate --- Analysis of variance --- Mathematical statistics --- Matrices --- Multivariate analysis --- Mathematical statistics. --- Statistique mathématique. --- Analyse multivariée.
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Mathematical statistics --- 519.237 --- Multivariate analysis --- statistiek --- multivariabele statistiek --- Multivariate distributions --- Multivariate statistical analysis --- Statistical analysis, Multivariate --- Analysis of variance --- Matrices --- Multivariate statistical methods --- Multivariate analysis. --- Methoden en technieken --- speciale methoden --- speciale methoden. --- 519.237 Multivariate statistical methods
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Mathematical statistics --- Multivariate analysis --- Multivariate analysis. --- 519.237 --- #SBIB:AANKOOP --- #SBIB:303H520 --- Multivariate distributions --- Multivariate statistical analysis --- Statistical analysis, Multivariate --- Analysis of variance --- Matrices --- Multivariate statistical methods --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- 519.237 Multivariate statistical methods
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519.237 --- Experimental design --- Multivariate analysis --- #WWIS:STAT --- Multivariate distributions --- Multivariate statistical analysis --- Statistical analysis, Multivariate --- Analysis of variance --- Mathematical statistics --- Matrices --- Design of experiments --- Statistical design --- Mathematical optimization --- Research --- Science --- Statistical decision --- Statistics --- Analysis of means --- 519.237 Multivariate statistical methods --- Multivariate statistical methods --- Experiments --- Methodology --- Experimental design. --- Multivariate analysis.
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In the last decade, graphical models have become increasingly popular as a statistical tool. This book is the first which provides an account of graphical models for multivariate complex normal distributions. Beginning with an introduction to the multivariate complex normal distribution, the authors develop the marginal and conditional distributions of random vectors and matrices. Then they introduce complex MANOVA models and parameter estimation and hypothesis testing for these models. After introducing undirected graphs, they then develop the theory of complex normal graphical models including the maximum likelihood estimation of the concentration matrix and hypothesis testing of conditional independence.
Distribution (Probability theory). --- Graph theory. --- Linear models (Statistics). --- Multivariate analysis.
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Mathematical models --- Models --- computer applications --- data collection --- Data processing --- Statistical methods --- time --- Multivariate analysis. --- Geology --- Analyse multivariée. --- Géostatistique. --- Statistical methods. --- Multivariate analysis --- 55.025 --- Multivariate distributions --- Multivariate statistical analysis --- Statistical analysis, Multivariate --- Analysis of variance --- Mathematical statistics --- Matrices --- Geological statistics --- Geostatistics --- Analyse multivariée --- Geology - Statistical methods --- Representation graphique --- Espace --- Methode numerique --- Geostatique
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Social representations --- Social sciences --- Multivariate analysis --- Factor analysis --- Statistical methods --- Social sciences - Statistical methods
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