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International Conference on Statistics, Combinatorics and Related Areas and the Eighth International Conference of Forum for Interdisciplinary Mathematics
December 19-21, 2001
School of Mathematics and Applied Statistics, University of Wollongong
Wollongong, NSW, Australia |
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Organizers
Satya N. Mishra (University of South Alabama), Chandra M. Gulati (University of Wollongong)
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Asymptotic Quasi-likelihood Based on Kernel Smoothing
by
Yan-Xia Lin
School of mathematics and Applied Statistics, University of Wollongong, Australia
Coauthors: Song Xi Chen (Department of Statistics and Applied Probability, National University of, Singapore)
Consider the application of
the asymptotic quasi-likelihood
technique to q-order markovian process model
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yt = m(yt-1, ..., yt-q;\theta) + \sigma(yt-1, ..., yt-q; \theta) \etat \hp0.5cm t >= 1. |
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This paper proves that, under fairly general conditions, the conditional
higher order moments E(ykt|Ft-1) can be well estimated
through Nadaraya-Watson
type estimators. By taking into account this fact, in this paper
we demonstrate
how the procedure of asymptotic quasi-likelihood works on q-order
markovian models. The study is carried out through
three examples. Comparisons between the estimates of \theta
obtained by the asymptotic quasi-likelihood method
and the maximum likelihood method (without checking but
assuming the conditional normal
distribution condition is held) are also presented.
Date received: November 13, 2001
Copyright © 2001 by the author(s).
The author(s) of this document and the organizers of the conference
have granted their consent to include this abstract in
Atlas Conferences Inc.
Document # caid-86.