Maximum quasi‐likelihood estimation for the near(2) model
Year: 2004
Type: article
Abstract: . Maximum quasi‐likelihood estimation is investigated for the NEAR(2) model, an autoregressive time series model with marginal exponential distributions. In certain regions of the parameter space, simulations indicate that maximum quasi‐likelihood estimators perform better than two‐stage conditional least squares estimators in terms of the per cent of estimates falling in the parameter space. The problem of out‐of‐range estimates is shown to be caused by the lack of information in the data rather than the characteristics of the method of estimation.
Source: Journal of Time Series Analysis
Author: S. Perera
Institution: University of Kansas Medical Center
Language: English
Subfield: Applied Mathematics
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
Funder: National Science Foundation
OpenAlex ID: W2078834909