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Palgrave Macmillan

The Foundations of Modern Time Series Analysis

ISBN 9780230290181
Publication Date September 2011
Formats Hardcover Ebook (EPUB) Ebook (PDF) 
Publisher Palgrave Macmillan
Series Palgrave Advanced Texts in Econometrics

This book is the first to develop the analysis of time series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication, Time Series Analysis; Forecasting and Control, in 1970, showing how these methods laid the foundations for the modern techniques of time series analysis that are in use today.

Many of the key examples and graphics found in the seminal articles of, for example, Schuster, Pearson, Yule, Slutzky and Kendall are recreated and the original voices of such authors are provided so that readers can become acquainted with the contemporary views, prejudices and hobby horses of the major protagonists in the story. Separate strands of developments are drawn together to show that, by 1970, a coherent, technically sophisticated and essentially practical body of knowledge was available for analyzing time series data coming from any discipline.

This book is essential reading for postgraduate students in time series analysis and time series econometrics.

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).

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


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