Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.
Автор: Koller Daphne, Friedman Nir Название: Probabilistic Graphical Models: Principles and Techniques ISBN: 0262013193 ISBN-13(EAN): 9780262013192 Издательство: MIT Press Рейтинг: Цена: 21161.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.
Most tasks require a person or an automated system to reason -- to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.
Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.
Автор: Koch Название: Analysis of Multivariate and High-Dimensional Data ISBN: 0521887933 ISBN-13(EAN): 9780521887939 Издательство: Cambridge Academ Рейтинг: Цена: 10613.00 р. Наличие на складе: Поставка под заказ.
Описание: `Big data` poses challenges that require both classical multivariate methods and modern machine-learning techniques. This coherent treatment integrates theory with data analysis, visualisation and interpretation of the analysis. Problems, data sets and MATLAB (R) code complete the package. It is suitable for master`s/graduate students in statistics and working scientists in data-rich disciplines.
Описание: Random matrix theory has a long history, beginning in the first instance in multivariate statistics. It was used by Wigner to supply explanations for the important regularity features of the apparently random dispositions of the energy levels of heavy nuclei. This title contains chapters which serve as an introduction into this area of research.
Автор: H?rdle Название: Multivariate Statistics: ISBN: 0387707840 ISBN-13(EAN): 9780387707846 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The authors present tools and concepts of multivariate data analysis by means of exercises and their solutions. The first part is devoted to graphical techniques. The second part deals with multivariate random variables and presents the derivation of estimators and tests for various practical situations. The last part introduces a wide variety of exercises in applied multivariate data analysis. The book demonstrates the application of simple calculus and basic multivariate methods in real life situations. It contains altogether 234 solved exercises which can assist a university teacher in setting up a modern multivariate analysis course. All computer-based exercises are available in the R or XploRe languages. The corresponding libraries are downloadable from the Springer link web pages and from the author’s home pages.
Описание: An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series.
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