The Foundations of Modern Time Series Analysis
Published on 29. June 2011
Book
Hardback
XIV, 461 pages
978-0-230-29018-1 (ISBN)
Description
This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.
More details
Series
Edition
2011 edition
Language
English
Place of publication
London
United Kingdom
Target group
Professional and scholarly
Product notice
Unsewn / adhesive bound
Paper over boards
Illustrations
XIV, 461 p.
Dimensions
Height: 243 mm
Width: 164 mm
Thickness: 32 mm
Weight
852 gr
ISBN-13
978-0-230-29018-1 (9780230290181)
DOI
10.1057/9780230305021
Schweitzer Classification
Other editions
Additional editions
Terence C. Mills
The Foundations of Modern Time Series Analysis
E-Book
06/2011
1st Edition
Palgrave Macmillan
€96.29
Available for download
Terence C. Mills
The Foundations of Modern Time Series Analysis
Book
01/2011
Palgrave Macmillan
€106.99
Shipment within 15-20 days
Person
TERENCE MILLS is Professor of Applied Statistics and Econometrics at Loughborough University, UK, having previously held professorial appointments at City University Business School and the University of Hull, UK. He has over 200 publications in a wide range of areas, including The Palgrave Handbook of Econometrics, Volumes 1 and 2 (co-edited with Kerry Patterson).
Content
Prolegomenon: A Personal Perspective and an Explanation of the Structure of the Book Yule and Hooker and the Concepts of Correlation and Trend Schuster, Beveridge and Periodogram Analysis Detrending and the Variate Difference Method: Student, Pearson and their Critics Nonsense Correlations, Random Shocks and Induced Cycles: Yule, Slutzky and Working Periodicities in Sunspots and Air Pressure: Yule, Walker and the Modelling of Superposed Fluctuations and Disturbances The Formal Modelling of Stationary Time Series: Wold and the Russians Generalizations and Extensions of Stationary Autoregressive Models: from Kendall to Box and Jenkins Statistical Inference, Estimation and Model Building for Stationary Time Series Dealing with Nonstationarity: Detrending, Smoothing and Differencing Forecasting Nonstationary Time Series Modelling Dynamic Relationships Between Time Series Spectral Analysis of Time Series: the Periodogram Revisited and Reclaimed Tacking Seasonal Patterns in Time Series Emerging Themes The Scene is Set References