Adaptive estimation in partially linear autoregressive models

DOI10.2307/3315966zbMath0961.62074OpenAlexW1976451055MaRDI QIDQ4527900

Thomas W. Yee, J. T. Gao

Publication date: 5 June 2001

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/421ad1ccf9dd7f5af7cf15cafe0e4af6d81b4716

zbMATH Keywords

dependent processesadaptive estimationnonlinear time seriesstrict stationaritypartially linear autoregression

Mathematics Subject Classification ID

Related Items (9)

Difference based estimation for partially linear regression models with measurement errors ⋮ Empirical likelihood-based subset selection for partially linear autoregressive models ⋮ Semiparametric methods in nonlinear time series analysis: a selective review ⋮ On a partly linear autoregressive model with moving average errors ⋮ Statistical inference on regression with spatial dependence ⋮ PARAMETER ESTIMATION IN A PARTLY LINEAR REGRESSION MODEL WITH RANDOM COEFFICIENT AUTOREGRESSIVE ERRORS ⋮ Empirical likelihood confidence regions for autoregressive models with explanatory variables ⋮ Semiparametric Autoregressive Conditional Duration Model: Theory and Practice ⋮ Model specification tests in nonparametric stochastic regression models

Cites Work

• Note on the uniform convergence of density estimates for mixing random variables
• Nonparametric curve estimation from time series
• KERNEL REGRESSION SMOOTHING OF TIME SERIES
• Asymptotic distribution of data‐driven smoothers in density and regression estimation under dependence
• Convergence of stochastic processes
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