Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1148772 | Journal of Statistical Planning and Inference | 2013 | 15 Pages |
Abstract
This paper describes an estimating function approach for parameter estimation in linear and nonlinear times series models with infinite variance stable errors. Joint estimates of location and scale parameters are derived for classes of autoregressive (AR) models and random coefficient autoregressive (RCA) models with stable errors, as well as for AR models with stable autoregressive conditionally heteroscedastic (ARCH) errors. Fast, on-line, recursive parametric estimation for the location parameter based on estimating functions is discussed using simulation studies. A real financial time series is also discussed in some detail.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
A. Thavaneswaran, N. Ravishanker, Y. Liang,