A Nonparametric Test for the Parallelism of Two First-Order Autoregressive Processes

DOI10.1111/1467-842X.00061zbMath0913.62045OpenAlexW1603407289MaRDI QIDQ4237746

Jiin-Huarng Guo

Publication date: 10 June 1999

Published in: Australian <html_ent glyph="@amp;" ascii="&amp;"/> New Zealand Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-842x.00061

zbMATH Keywords

bootstrap methodparallelismasymptotic relative efficiencyMann-Whitney statisticefficacyfirst-order autoregressive processes

Mathematics Subject Classification ID

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

Related Items (12)

Assessing One-Step-Ahead Prediction Error Based on the Median for First-Order Autoregressive Models in the Presence Of Outliers ⋮ Comparing non-stationary and irregularly spaced time series ⋮ Testing for Equal Predictability of Stationary ARMA Processes ⋮ COMPARING TIME-VARYING AUTOREGRESSIVE STRUCTURES OF LOCALLY STATIONARY PROCESSES ⋮ Comparison of stationary time series using distribution-free methods ⋮ Pattern Recognition of Time Series using Wavelets ⋮ A test to compare interval time series ⋮ USING WAVELETS TO COMPARE TIME SERIES PATTERNS ⋮ Comparison of time series using subsampling ⋮ A test for comparing two discrete stochastic dynamical systems under heteroskedasticity ⋮ Robust estimation for the coefficient of a first order autoregressive process ⋮ Comparison of non-stationary time series in the frequency domain

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