Adaptive estimation in partially linear autoregressive models
- 1 September 2000
- journal article
- Published by Wiley in The Canadian Journal of Statistics / La Revue Canadienne de Statistique
- Vol. 28 (3) , 571-586
- https://doi.org/10.2307/3315966
Abstract
The authors consider a partially linear autoregressive model and construct kernel‐based estimates for both the parametric and nonparametric components. They propose an estimation procedure for the model and illustrate it through simulated and real data. Their work shows that the proposed estimation procedure not only has good asymptotic properties but also works well numerically. It also suggests that a partially linear autoregression is more appropriate than a completely nonparametric autoregression for some sets of data.Keywords
This publication has 17 references indexed in Scilit:
- Partially Linear ModelsPublished by Springer Nature ,2000
- Asymptotic distribution of data‐driven smoothers in density and regression estimation under dependenceThe Canadian Journal of Statistics / La Revue Canadienne de Statistique, 1995
- Asymptotic normality of pseudo-LS estimator for partly linear autoregression modelsStatistics & Probability Letters, 1995
- ARCH MODELS: PROPERTIES, ESTIMATION AND TESTINGJournal of Economic Surveys, 1993
- Nonlinear Additive ARX ModelsJournal of the American Statistical Association, 1993
- KERNEL REGRESSION SMOOTHING OF TIME SERIESJournal of Time Series Analysis, 1992
- Data-Driven Bandwidth Choice for Density Estimation Based on Dependent DataThe Annals of Statistics, 1990
- Nonparametric Curve Estimation from Time SeriesPublished by Springer Nature ,1989
- Convergence Rates for Parametric Components in a Partly Linear ModelThe Annals of Statistics, 1988
- From Clocks to ChaosPublished by Walter de Gruyter GmbH ,1988