Testing for Parallelism Among Trends in Multiple Time Series

DOI10.1109/TSP.2011.2177831zbMath1391.62164OpenAlexW2093530499MaRDI QIDQ4573586

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Publication date: 18 July 2018

Published in: IEEE Transactions on Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/tsp.2011.2177831

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: hypothesis testing (62M07)

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Unnamed Item ⋮ Clustering High-Dimensional Time Series Based on Parallelism ⋮ On detecting non‐monotonic trends in environmental time series: a fusion of local regression and bootstrap ⋮ Kernel-Based Partial Permutation Test for Detecting Heterogeneous Functional Relationship ⋮ Identifying shifts between two regression curves ⋮ Testing for Equality of an Increasing Number of Spectral Density Functions ⋮ A local factor nonparametric test for trend synchronism in multiple time series ⋮ Multiscale clustering of nonparametric regression curves ⋮ VAR model based clustering method for multivariate time series data ⋮ Testing for Trends in High-Dimensional Time Series ⋮ Nonparametric comparison of epidemic time trends: the case of COVID-19 ⋮ Testing for jumps in the presence of smooth changes in trends of nonstationary time series

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