Time Series Analysis

ARMA, state-space models, and nonstationary time series.

foundation tier

Time Series Analysis. ARMA, state-space models, and nonstationary time series. This page collects canonical references that organise the subject and provide entry points to its main techniques.

Foundations and canonical references

The standard treatments of time series analysis approach the subject from complementary angles. Box, Time Series Analysis: Forecasting and Control (2015) is the anchor reference for the subject and lays out the core definitions, theorems, and worked examples that practitioners return to. Hamilton, Time Series Analysis (1994) gives a parallel, more proof-oriented exposition of the same material and is widely used as a graduate text.

Open methodological questions for time series analysis include sharpening the bridges between foundational theory and computational practice, extending classical results to broader or more structured settings, and integrating the techniques surveyed above with adjacent mathematical disciplines. The references listed in this page are the entry points that current work builds on.

Prerequisites

Sources

  • textbook · primary · 2015
    Time Series Analysis: Forecasting and Control
    box-2015, jenkins-2015, reinsel-2015, ljung-2015
  • textbook · primary · 1994
    Time Series Analysis
    hamilton-1994

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Explore

  1. 01

    State-Space Models and Filtering

    Kalman and particle filters for hidden-state inference.
  2. 02

    Spectral Analysis of Time Series

    Periodograms, multitaper methods, and long-memory processes.

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