Goodness-of-Fit Statistics for Discrete Multivariate Data, Timothy R.C. Read; Noel A.C. Cressie

Автор: Koch
Название: Analysis of Multivariate and High-Dimensional Data
ISBN: 0521887933 ISBN-13(EAN): 9780521887939
Издательство: Cambridge Academ
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Цена: 70750.00 T
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.

Автор: Miller Jane E.
Название: The Chicago Guide to Writing about Multivariate Analysis, Second Edition
ISBN: 0226527875 ISBN-13(EAN): 9780226527871
Издательство: Wiley
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Цена: 44350.00 T
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Описание: Suitable for those who needs to communicate complex research results, this title includes four new chapters that cover writing about interactions, writing about event history analysis, writing about multilevel models, and the "Goldilocks principle" for choosing the right size contrast for interpreting results for different variables.

Автор: Ruey S. Tsay
Название: Multivariate Time Series Analysis: With R and Financial Applications
ISBN: 1118617908 ISBN-13(EAN): 9781118617908
Издательство: Wiley
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Цена: 125610.00 T
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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.

Автор: Wickens
Название: The Geometry of Multivariate Statistics
ISBN: 1138882828 ISBN-13(EAN): 9781138882829
Издательство: Taylor&Francis
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Цена: 58170.00 T
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Описание: A traditional approach to developing multivariate statistical theory is algebraic. Sets of observations are represented by matrices, linear combinations are formed from these matrices by multiplying them by coefficient matrices, and useful statistics are found by imposing various criteria of optimization on these combinations. Matrix algebra is the vehicle for these calculations. A second approach is computational. Since many users find that they do not need to know the mathematical basis of the techniques as long as they have a way to transform data into results, the computation can be done by a package of computer programs that somebody else has written. An approach from this perspective emphasizes how the computer packages are used, and is usually coupled with rules that allow one to extract the most important numbers from the output and interpret them. Useful as both approaches are--particularly when combined--they can overlook an important aspect of multivariate analysis. To apply it correctly, one needs a way to conceptualize the multivariate relationships that exist among variables. This book is designed to help the reader develop a way of thinking about multivariate statistics, as well as to understand in a broader and more intuitive sense what the procedures do and how their results are interpreted. Presenting important procedures of multivariate statistical theory geometrically, the author hopes that this emphasis on the geometry will give the reader a coherent picture into which all the multivariate techniques fit.

Автор: H?rdle
Название: Multivariate Statistics:
ISBN: 0387707840 ISBN-13(EAN): 9780387707846
Издательство: Springer
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Цена: 55890.00 T
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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.

Автор: Whittaker, Joe
Название: Graphical models in applied multivariate statistics
ISBN: 0470743662 ISBN-13(EAN): 9780470743669
Издательство: Wiley
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Цена: 70700.00 T
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Описание: - It reveals the interrelationships between multiple variables and features of the underlying conditional independence. - It covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. - Many numerical examples and exercises with solutions are included.

Автор: Wolfgang Karl H?rdle; Zden?k Hl?vka
Название: Multivariate Statistics
ISBN: 3642360041 ISBN-13(EAN): 9783642360046
Издательство: Springer
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Цена: 55890.00 T
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Описание: This book presents the tools and concepts of multivariate data analysis. It demonstrates the application of simple calculus and basic multivariate methods in real life situations, and features more than 200 solved exercises.

Автор: T. W. Anderson
Название: An Introduction to Multivariate Statistical Analysis, Third Edition
ISBN: 0471360910 ISBN-13(EAN): 9780471360919
Издательство: Wiley
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Цена: 184750.00 T
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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: Bai Zhidong Et Al
Название: Random Matrix Theory And Its Applications: Multivariate Statistics And Wireless Communications
ISBN: 9814273112 ISBN-13(EAN): 9789814273114
Издательство: World Scientific Publishing
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Цена: 80250.00 T
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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.