Multivariate Time Series With Linear State Space Structure, V?ctor G?mez

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: 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.

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
Наличие на складе: Невозможна поставка.
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: W. Hennevogl; Ludwig Fahrmeir; Gerhard Tutz
Название: Multivariate Statistical Modelling Based on Generalized Linear Models
ISBN: 1441929002 ISBN-13(EAN): 9781441929006
Издательство: Springer
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Цена: 181670.00 T
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Описание: The book is aimed at applied statisticians, graduate students of statistics, and students and researchers with a strong interest in statistics and data analysis. This second edition is extensively revised, especially those sections relating with Bayesian concepts.

Автор: Simon P. Burke; John Hunter; Alessandra Canepa
Название: Multivariate Modelling of Non-Stationary Economic Time Series
ISBN: 0230243304 ISBN-13(EAN): 9780230243309
Издательство: Springer
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Цена: 186330.00 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.

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.

Автор: Zhihua Zhang
Название: Multivariate Time Series Analysis in Climate and Environmental Research
ISBN: 3319673394 ISBN-13(EAN): 9783319673394
Издательство: Springer
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Цена: 139750.00 T
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Описание: This book offers comprehensive information on the theory, models and algorithms involved in state-of-the-art multivariate time series analysis and highlights several of the latest research advances in climate and environmental science. The main topics addressed include Multivariate Time-Frequency Analysis, Artificial Neural Networks, Stochastic Modeling and Optimization, Spectral Analysis, Global Climate Change, Regional Climate Change, Ecosystem and Carbon Cycle, Paleoclimate, and Strategies for Climate Change Mitigation. The self-contained guide will be of great value to researchers and advanced students from a wide range of disciplines: those from Meteorology, Climatology, Oceanography, the Earth Sciences and Environmental Science will be introduced to various advanced tools for analyzing multivariate data, greatly facilitating their research, while those from Applied Mathematics, Statistics, Physics, and the Computer Sciences will learn how to use these multivariate time series analysis tools to approach climate and environmental topics.