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brito p dias s analysis distributional data 2022

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Textbook in PDF format Data where for each entity and variable a distribution is given is called distributional data. In the era of "Big Data," this type of data is becoming more and more prevalent. This edited book presents a synthesis of research in this area over the last twenty years or so. It has been carefully edited to ensure it is consistent with respect to style, level, notation, etc. Each chapter includes real data examples to illustrate the topics and software where appropriate. Preface About the Editors List of Figures List of Tables Contributors Data Representation and Exploratory Analysis Fundamental Concepts about Distributional Data Descriptive Statistics based on Frequency Distribution Descriptive Statistics for Numeric Distributional Data The Quantile Methods to Analyze Distributional Data Clustering and Classi cation Partitive and Hierarchical Clustering of Distributional Datausing the Wasserstein Distance Divisive Clustering of Histogram Data Clustering of Modal Valued Data Mixture Models for Distributional Data Classication of Continuous Distributional Data Using the Logratio Approach Dimension Reduction Principal Component Analysis of Distributional Data Principal Component Analysis of Numeric Distributional Data Multidimensional Scaling of Distributional Data Regression and Forecasting Regression Analysis with the Distribution and Symmetric Distribution Model Regression Analysis of Distributional Data Based on a Two-Component Model Forecasting Distributional Time Series

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Brito P., Dias S. Analysis of Distributional Data 2022.pdf 14.0 MB

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brito p dias s analysis distributional data 2022