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Advances in Multivariate Data Analysis
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290 b
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The book presents a range of new developments in the theory and practice of multivariate statistical data analysis. Among the topics are the construction and comparison of classification trees, clustering methods, generalized multivariate distributions, the analysis of symbolic data, explorative time series analysis, smoothing and dynamic regression models, generalized linear models, and neural networks. Several contributions illustrate the use of multivariate methods in application fields such as economics, medicine, environment, and biology. TOC:Classification Methods with Applications.- Time Series Analysis and Related Methods.- Computer Intensive Techniques and Algorithms.- Classification and Data Analysis in Economics.- Multivariate Analysis in Applied Sciences.- Author Index.- Subject Index.
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Angielski
