## Abstract We consider the use of generalized additive models with correlated errors for analysing trends in time series. The trend is represented as a smoothing spline so that it can be extrapolated. A method is proposed for choosing the smoothing parameter. It is based on the ability to predict
Generalized smoothed estimating functions for nonlinear time series
โ Scribed by A. Thavaneswaran; Shelton Peiris
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 208 KB
- Volume
- 65
- Category
- Article
- ISSN
- 0167-7152
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โฆ Synopsis
This note considers a new class of nonparametric estimators for nonlinear time-series models based on kernel smoothers. Various new results are given for two popular nonlinear time-series models and compared with the results of Thavaneswaran and Peiris (Statist. Probab. Lett. 28 (1996) 227).
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