Applied time series analysis: a practical guide to modeling and forecasting

✍ Scribed by Mills, Terence C

Publisher: Elsevier,Academic Press
Year: 2019
Tongue: English
Leaves: 337
Category: Library

No coin nor oath required. For personal study only.

✦ Table of Contents

Content: Time series and their features --
Transforming time series --
ARMA models for stationary time series --
ARIMA models for nonstationary time series --
Unit roots, difference and trend stationarity, and fractional differencing --
Breaking and nonlinear trends --
An introduction to forecasting with univariate models --
Unobserved component models, signal extraction, and filters --
Seasonality and exponential smoothing --
Volatility and generalized autoregressive conditional heteroskedastic processes --
Nonlinear stochastic processes --
Transfer functions and autoregressive distributed lag modeling --
Vector autoregressions and Granger causality --
Error corection, spurious regressions, and cointegration --
Vector autoregressions with integrated variables, vector error correction models, and common trends --
Compositional and count time series --
State space models.

✦ Subjects

Time-series analysis.

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