Introduction to statistical time series

Introduction to statistical time series

by Wayne A. Fuller

Part of Wiley series in probability and statistics

1996
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About
The subject of time series is of considerable interest, especiallyamong researchers in econometrics, engineering, and the naturalsciences. As part of the prestigious Wiley Series in Probabilityand Statistics, this book provides a lucid introduction to thefield and, in this new Second Edition, covers the importantadvances of recent years, including nonstationary models, nonlinearestimation, multivariate models, state space representations, andempirical model identification. New sections have also been addedon the Wold decomposition, partial autocorrelation, long memoryprocesses, and the Kalman filter.

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  1. 1

    How does Fuller’s approach to structuring the fundamentals of time series analysis shape a reader's foundational understanding compared to learning through applied software alone?

  2. 2

    Reflecting on the balance between theory and application in your own field, how do you bridge the gap between abstract statistical models like the Wold decomposition and real-world messy data?

  3. 3

    Fuller emphasizes the evolution into nonstationary models and nonlinear estimation; how has your own perception of randomness and predictability shifted as you’ve encountered more complex data sets in your career or studies?

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