A data-driven test to compare two or multiple time series
From MaRDI portal
Publication:901611
DOI10.1016/j.csda.2011.01.013zbMath1328.62508OpenAlexW2071431296MaRDI QIDQ901611
Publication date: 12 January 2016
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2011.01.013
autocorrelationstationary time seriesheavy-taileddata-drivengeneralized scoretapered periodogramvibration data
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (8)
Autoregressive functions estimation in nonlinear bifurcating autoregressive models ⋮ A test for the equality of monotone transformations of two random variables ⋮ A computational bootstrap procedure to compare two dependent time series ⋮ Tests for the Equality of Two Processes' Spectral Densities with Unequal Lengths Using Wavelet Methods ⋮ Robust tests for time series comparison based on Laplace periodograms ⋮ Wavelet‐Based Tests for Comparing Two Time Series with Unequal Lengths ⋮ A New Test for Checking the Equality of the Correlation Structures of two time Series ⋮ Comparing autocorrelation structures of multiple time series via the maximum distance between two groups of time series
Cites Work
- Comparison of time series using subsampling
- A periodogram-based metric for time series classification
- Misspecified models with dependent observations
- Time series: theory and methods.
- A necessary and sufficient condition for asymptotic independence of discrete Fourier transforms under short- and long-range dependence
- A DISTANCE MEASURE FOR CLASSIFYING ARIMA MODELS
- Testing equality of stationary autocovariances
- SPECTRAL ANALYSIS WITH TAPERED DATA
- Comparison of Times Series with Unequal Length in the Frequency Domain
- TESTS FOR COMPARING TWO ESTIMATED SPECTRAL DENSITIES
- A mean squared error criterion for time series data windows
- Non-linear time series models for non-linear random vibrations
- Testing lack of fit in multiple regression
This page was built for publication: A data-driven test to compare two or multiple time series
