Recent Developments in Recursive Estimation for Time Series Models
- You Liang
- A. Thavaneswaran
- B. Abraham
Abstract
Recently there has been a growing interest in joint estimation of the location and scale parameters using combined estimation functions. Combined estimating functions had been studied in Liang et al. (2011) for models with finite variance errors and in Thavaneswaran et al. (2013) for models with infinite variancestable errors. In this paper, first a theorem on recursive estimation based on estimating functions is extended to multi-parameter setup and it is shown that the unified approach can be used to estimate the location parameter recursively for models with finite variance/infinite variance errors. The method is applied for the joint estimation of the location and scale parameters for regression models with ARCH errors and RCA models with GARCH errors.
- Full Text: PDF
- DOI:10.5539/ijsp.v5n2p59
This work is licensed under a Creative Commons Attribution 4.0 License.
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