A test for second-order stationarity of a time series based on the maximum of Anderson-Darling statistics

DOI10.1016/j.jspi.2021.02.010zbMath1477.62144OpenAlexW3164828357MaRDI QIDQ2242849

Shibin Zhang

Publication date: 10 November 2021

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2021.02.010

zbMATH Keywords

periodogramspectral densityAnderson-Darling statisticspectral comparisontest for stationarity

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Hypothesis testing in multivariate analysis (62H15) Inference from stochastic processes and spectral analysis (62M15)

Related Items

Tests for comparing time‐invariant and time‐varying spectra based on the Anderson–Darling statistic

Uses Software

• BayesSpec

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Testing temporal constancy of the spectral structure of a time series
• On the rate of convergence in the multivariate CLT
• On the detection of changes in autoregressive time series. I: Asymptotics.
• Locally adaptive estimation of evolutionary wavelet spectra
• Time series: theory and methods.
• Fitting time series models to nonstationary processes
• A test for second order stationarity of a multivariate time series
• A test for stationarity based on empirical processes
• Testing stationarity of functional time series
• Local inference for locally stationary time series based on the empirical spectral measure
• A Wavelet-Based Test for Stationarity
• On Local Power Properties of Frequency Domain‐based Tests for Stationarity
• A Measure of Stationarity in Locally Stationary Processes With Applications to Testing
• Structural Breaks in Financial Time Series
• A Method for Simulating Stable Random Variables
• Tests for Comparing Time‐Invariant and Time‐Varying Spectra Based on the Pearson Statistic
• AdaptSPEC: Adaptive Spectral Estimation for Nonstationary Time Series
• A test for second-order stationarity of a time series based on the discrete Fourier transform
• Adaptive Bayesian Time–Frequency Analysis of Multivariate Time Series
• Detection of Multiple Structural Breaks in Multivariate Time Series
• Detection of Changes in Multivariate Time Series With Application to EEG Data
• A Test for Stationarity for Irregularly Spaced Spatial Data
• Asymptotic Theory of Certain "Goodness of Fit" Criteria Based on Stochastic Processes
• A Test of Goodness of Fit
• Time Series