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Abstract The definition of stationary time series was first provided followed by a few examples of nonstationary time series. Statistical methods to analyze nonstationary time series was then reviewed in two categories: parametric methods and nonparametric methods. Focus was given to nonparametric methods. Spectral analysis of time series with seasonal components was discussed as a special case. Copyright © 2010 John Wiley & Sons, Inc. This article is categorized under: Data: Types and Structure > Time Series, Stochastic Processes, and Functional Data

The logarithm of raw ozone daily maxima time series separated into two components, short‐term variations (residuals), and filtered log of ozone (KZ29, 3), including both true seasonal and long‐term trend components.

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Plots of raw data (a) and reconstructed signal (b) using two‐dimensional KZA. The true signal is one unit at 30 < x, y < 70 and 0 otherwise.

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Plots of the original time series (a) and KZA reconstruction of the true signal (b).

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Data: Types and Structure > Time Series, Stochastic Processes, and Functional Data

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