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MATH5802M Time Series and Spectral Analysis

This class was created by Brainscape user Sophie Wilkinson. Visit their profile to learn more about the creator.

By: Sophie Wilkinson
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Decks in this class (7)

Introduction and Stationary Processes
fitting a trend, seasonal effects, stationary processes
29  cards
Models for Time Series
white noise, moving average models, autoregressive models, mixed autoregressive moving average (ARMA) models, integrated models
42  cards
Model Fitting
model selection, parameter estimation (method of moments, least squares, MLE), MOM and invertibility for MA
23  cards
Forecasting
minimum mean square, model based forecasting
31  cards
Fitting Sine Waves and Computing the Periodogram
frequency, aliasing, the DFT, spectral density and periodogram
24  cards
DFT for Time Series
spectral density and autocovariance, spectral density of white noise, spectral density of AR(p)
15  cards
Complications
smoothing the periodogram, inconsistency, truncating the autocovariance function, smoothing the raw periodogram, spectral window, spectral linkage, harmonics
29  cards

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MATH5802M Time Series and Spectral Analysis

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