Multivariate Stat Modeling In Engin, Jhareswar Maiti

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: 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: Pituch Keenan A
Название: Applied Multivariate Statistics for the Social Sciences
ISBN: 0415836662 ISBN-13(EAN): 9780415836661
Издательство: Taylor&Francis
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Цена: 117390.00 T
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Описание: Noted for its breadth and depth of coverage of multivariate statistics and its emphasis on power, this classic text focuses on a conceptual understanding of the material rather than on proving results. Numerous examples, along with use of SAS and SPSS, indicate what the numbers mean and how to interpret the results.

Название: Copulae and Multivariate Probability Distributions in Finance
ISBN: 0415814855 ISBN-13(EAN): 9780415814850
Издательство: Taylor&Francis
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Цена: 91860.00 T
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Описание: This book provides a synthesis of the latest research in the area of copulae as applied to finance and related subjects such as insurance. It describes the state of the art in the tools required to deal with these observed features of financial data. This book was originally published as a special issue of the European Journal of Finance.

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
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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: 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: Simon P. Burke; John Hunter; Alessandra Canepa
Название: Multivariate Modelling of Non-Stationary Economic Time Series
ISBN: 0230243312 ISBN-13(EAN): 9780230243316
Издательство: Springer
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Цена: 55890.00 T
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Описание: This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models.