Global property of error density estimation in nonlinear autoregressive time series models

DOI10.1007/s11203-009-9036-9zbMath1205.62038OpenAlexW2014800944MaRDI QIDQ625315

Fuxia Cheng

Publication date: 15 February 2011

Published in: Statistical Inference for Stochastic Processes (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11203-009-9036-9

zbMATH Keywords

stationary processnonlinear autoregressive modelresidualserror density estimationglobal measure

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20)

Related Items (5)

Law of the iterated logarithm for error density estimators in nonlinear autoregressive models ⋮ Asymptotic normality of residual density estimator in stationary and explosive autoregressive models ⋮ Revisiting the estimation of the error density in functional autoregressive models ⋮ Strong consistency of the distribution estimator in the nonlinear autoregressive time series ⋮ Strong uniform consistency and asymptotic normality of a kernel based error density estimator in functional autoregressive models

Cites Work

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• On conditional least squares estimation for stochastic processes
• Estimating the density of the residuals in autoregressive models
• Weighted empirical processes in dynamic nonlinear models.
• On the Bickel-Rosenblatt test for first-order autoregressive models
• On some global measures of the deviations of density function estimates
• A goodness-of-fit test of the errors in nonlinear autoregressive time series models
• Weighted sums of certain dependent random variables
• Estimation of the Distribution of Noise in an Autoregression Scheme
• Asymptotics of the \(L_p\)-norms of density estimators in the first-order autoregressive models.

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