Temporal Aggregation of Univariate and Multivariate Time Series Models
Author: Andrea Silvestrini
Publisher:
Published: 2008
Total Pages: 68
ISBN-13:
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Time Series Analysis Univariate and Multivariate Methods
Author: William W. S. Wei
Publisher: Pearson
Published: 2018-03-14
Total Pages: 648
ISBN-13: 9780134995366
DOWNLOAD EBOOKWith its broad coverage of methodology, this comprehensive book is a useful learning and reference tool for those in applied sciences where analysis and research of time series is useful. Its plentiful examples show the operational details and purpose of a variety of univariate and multivariate time series methods. Numerous figures, tables and real-life time series data sets illustrate the models and methods useful for analyzing, modeling, and forecasting data collected sequentially in time. The text also offers a balanced treatment between theory and applications. Time Series Analysis is a thorough introduction to both time-domain and frequency-domain analyses of univariate and multivariate time series methods, with coverage of the most recently developed techniques in the field.
Multivariate Time Series Analysis and Applications
Author: William W. S. Wei
Publisher: John Wiley & Sons
Published: 2019-03-18
Total Pages: 536
ISBN-13: 1119502853
DOWNLOAD EBOOKAn essential guide on high dimensional multivariate time series including all the latest topics from one of the leading experts in the field Following the highly successful and much lauded book, Time Series Analysis—Univariate and Multivariate Methods, this new work by William W.S. Wei focuses on high dimensional multivariate time series, and is illustrated with numerous high dimensional empirical time series. Beginning with the fundamentalconcepts and issues of multivariate time series analysis,this book covers many topics that are not found in general multivariate time series books. Some of these are repeated measurements, space-time series modelling, and dimension reduction. The book also looks at vector time series models, multivariate time series regression models, and principle component analysis of multivariate time series. Additionally, it provides readers with information on factor analysis of multivariate time series, multivariate GARCH models, and multivariate spectral analysis of time series. With the development of computers and the internet, we have increased potential for data exploration. In the next few years, dimension will become a more serious problem. Multivariate Time Series Analysis and its Applications provides some initial solutions, which may encourage the development of related software needed for the high dimensional multivariate time series analysis. Written by bestselling author and leading expert in the field Covers topics not yet explored in current multivariate books Features classroom tested material Written specifically for time series courses Multivariate Time Series Analysis and its Applications is designed for an advanced time series analysis course. It is a must-have for anyone studying time series analysis and is also relevant for students in economics, biostatistics, and engineering.
Handbook of Economic Forecasting
Author: G. Elliott
Publisher: Elsevier
Published: 2006-07-14
Total Pages: 1071
ISBN-13: 0444513957
DOWNLOAD EBOOKSection headings in this handbook include: 'Forecasting Methodology; 'Forecasting Models'; 'Forecasting with Different Data Structures'; and 'Applications of Forecasting Methods.'.
Forecasting, Structural Time Series Models and the Kalman Filter
Author: Andrew C. Harvey
Publisher: Cambridge University Press
Published: 1990
Total Pages: 574
ISBN-13: 9780521405737
DOWNLOAD EBOOKA synthesis of concepts and materials, that ordinarily appear separately in time series and econometrics literature, presents a comprehensive review of theoretical and applied concepts in modeling economic and social time series.
Multivariate Time Series Analysis
Author: Ruey S. Tsay
Publisher: John Wiley & Sons
Published: 2013-11-11
Total Pages: 414
ISBN-13: 1118617754
DOWNLOAD EBOOKAn 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. Through a fundamental balance of theory and methodology, the book supplies readers with a comprehensible approach to financial econometric models and their applications to real-world empirical research. Differing from the traditional approach to multivariate time series, the book focuses on reader comprehension by emphasizing structural specification, which results in simplified parsimonious VAR MA modeling. Multivariate Time Series Analysis: With R and Financial Applications utilizes the freely available R software package to explore complex data and illustrate related computation and analyses. Featuring the techniques and methodology of multivariate linear time series, stationary VAR models, VAR MA time series and models, unitroot process, factor models, and factor-augmented VAR models, the book includes: • Over 300 examples and exercises to reinforce the presented content • User-friendly R subroutines and research presented throughout to demonstrate modern applications • Numerous datasets and subroutines to provide readers with a deeper understanding of the material Multivariate Time Series Analysis is an ideal textbook for graduate-level courses on time series and quantitative finance and upper-undergraduate level statistics courses in time series. The book is also an indispensable reference for researchers and practitioners in business, finance, and econometrics.
Mathematical Modelling of Contemporary Electricity Markets
Author: Athanasios Dagoumas
Publisher: Academic Press
Published: 2021-01-30
Total Pages: 444
ISBN-13: 0128218398
DOWNLOAD EBOOKMathematical Modelling of Contemporary Electricity Markets reviews major methodologies and tools to accurately analyze and forecast contemporary electricity markets in a ways that is ideal for practitioner and academic audiences. Approaches include optimization, neural networks, genetic algorithms, co-optimization, econometrics, E3 models and energy system models. The work examines how new challenges affect power market modeling, including discussions of stochastic renewables, price volatility, dynamic participation of demand, integration of storage and electric vehicles, interdependence with other commodity markets and the evolution of policy developments (market coupling processes, security of supply). Coverage addresses all major forms of electricity markets: day-ahead, forward, intraday, balancing, and capacity. - Provides a diverse body of established techniques suitable for modeling any major aspect of electricity markets - Familiarizes energy experts with the quantitative skills needed in competitive electricity markets - Reviews market risk for energy investment decisions by stressing the multi-dimensionality of electricity markets
Non-Linear Time Series Models in Empirical Finance
Author: Philip Hans Franses
Publisher: Cambridge University Press
Published: 2000-07-27
Total Pages: 299
ISBN-13: 0521770416
DOWNLOAD EBOOKThis 2000 volume reviews non-linear time series models, and their applications to financial markets.
Time-Series Forecasting
Author: Chris Chatfield
Publisher: CRC Press
Published: 2000-10-25
Total Pages: 281
ISBN-13: 1420036203
DOWNLOAD EBOOKFrom the author of the bestselling "Analysis of Time Series," Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods. It provides a summary of time-series modelling procedures, followed by a brief catalogue of many different time-series forecasting methods, ranging from ad-hoc methods through ARIMA and state-space
