Autoregression quantiles and related rank score processes for generalized random coefficient autoregressive processes.

DOI10.1016/S0378-3758(97)00145-6zbMath1067.62570MaRDI QIDQ1299546

Michel Harel, Madan Lal Puri

Publication date: 1998

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

zbMATH Keywords

Absolute regularityAutoregression quantilesGeneralized random coefficient autoregressive processRelated rank scores processesStrong mixing

Mathematics Subject Classification ID

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

Related Items (2)

The marked empirical process to test nonlinear time series against a large class of alternatives when the random vectors are nonstationary and absolutely regular ⋮ Une méthode semi-paramétrique pour tester un modèle de régression. (A semi-parametric method to test a regression model)

Cites Work

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• Bilinear Markovian representation and bilinear models
• Asymptotic behavior of regression quantiles in non-stationary, dependent cases
• Regression rank scores and regression quantiles
• A weak convergence result useful in robust autoregression
• Convergence of empirical processes of mixing rv's on \([0,1\)]
• Weak convergence of randomly weighted dependent residual empiricals with applications to autoregression
• The mixing property of bilinear and generalised random coefficient autoregressive models
• Limiting behavior of U-statistics, V-statistics, and one sample rank order statistics for nonstationary absolutely regular processes
• Autoregression quantiles and related rank-scores processes
• Estimation in a linear model based on regression rank scores
• Tests of linear hypotheses based on regression rank scores
• SUR UN MODÉLE AUTORÉGRESSIF NON LINÉAIRE, ERGODICITÉ ET ERGODICITÉ GÉOMÉTRIQUE
• Regression Quantiles

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