Publication Date
3-15-1979
Abstract
Stochastic approximation methods for estimating the parameters of a stationary autoregressive process of finite order are investigated. The emphasis is on robust methods, and the non-linear scoring functions associated with such methods require the development of new techniques for establishing convergence. A mixing condition falling between the traditional strong and uniform mixing conditions is investigated in detail, and used to establish almost sure and mean square convergence of the proposed algorithms when the underlying process satisfies this condition. A short Monte Carlo study verifies the desirable properties of the robust algorithm in the presence of heavy-tailed innovations.
Degree Name
Mathematics
Level of Degree
Doctoral
Department Name
Mathematics & Statistics
First Committee Member (Chair)
Lambert Herman Koopmans
Second Committee Member
Clifford Ray Qualls
Third Committee Member
Pramod Kumar Pathak
Language
English
Document Type
Dissertation
Recommended Citation
Campbell, Katherine. "Stochastic Approximation Procedures For Mixing Stochastic Processes." (1979). https://digitalrepository.unm.edu/math_etds/225
