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Shrinkage strategies in some multiple multi-factor dynamical systems

Published online by Cambridge University Press:  03 July 2012

Sévérien Nkurunziza*
Affiliation:
University of Windsor, 401 Sunset Avenue, Windsor, N9B 3P4, Ontario, Canada. [email protected]
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Abstract

In this paper, we are interested in estimation problem for the drift parameters matrices of m independent multivariate diffusion processes. More specifically, we consider the case where the m-parameters matrices are supposed to satisfy some uncertain constraints. Given such an uncertainty, we develop shrinkage estimators which improve over the performance of the maximum likelihood estimator (MLE). Under an asymptotic distributional quadratic risk criterion, we study the relative dominance of the established estimators. Further, we carry out simulation studies for observation periods of small and moderate lengths of time that corroborate the theoretical finding for which shrinkage estimators outperform over the MLE. The proposed method is useful in model assessment and variable selection.

Type
Research Article
Copyright
© EDP Sciences, SMAI, 2012

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References

Références

S.E. Ahmed, Shrinkage estimation of regression coefficients from censored data with multiple observations, in Empirical Bayes and Likelihood inference, edited by S.E. Ahmed and N. Reid. Springer, New York (2001) 103–120.
Ahmed, S.E. and Saleh, A.K.Md.E., Improved nonparametric estimation of location vector in a multivariate regression model. J. Nonparametr. Stat. 11 (1999) 5178. Google Scholar
A.R. Bergstrom, Continuous Time Econometric Modelling. Oxford University Press, Oxford (1990).
A. DasGupta, Asymptotic theory of statistics and probability. Springer Science & Business Media, New York (2008).
De Gunst, M.C.M., On the distribution of general quadratic functions in normal vectors. Stat. Neerl. 41 (1987) 245251. Google Scholar
Engen, S., Lande, R., Wall, T. and DeVries, J.P., Analyzing spatial structure of communities using the two-dimensional Poisson lognormal species abundance model. The American Naturalist 160 (2002) 6073. Google Scholar
S. Iyengar, Diffusion models for neutral activity, in Statistics for the 21st Century : Methodologies for Applications of the Future, edited by C.R. Rao and G. Szekely. Marcel-Dekker (2000) 233–250.
A.J. Izenman, Modern Multivariate Statistical Techniques : Regression, Classification, and Manifold Learning. Springer Science, Business Media, LLC (2008).
G.G. Judge and M.E. Bock, The statistical implication of pre-test and Stein-rule estimators in econometrics. Amsterdam, North Holland (1978).
I. Karatzas and S.E. Shreve, Brownian Motion and Stochastic Calculus. Springer-Verlag, New York (1991).
A.Y. Kutoyants, Statistical Inference for Ergodic Diffusion Processes, in Springer Series in Statistics. Springer-Verlag, London (2004).
R.S. Liptser and A.N. Shiryaev, Statistics of Random Processes : Generale Theory I. Springer-Verlag, New York (1977).
R.S. Liptser and A.N. Shiryaev, Statistics of Random Processes : Applications II. Springer-Verlag, New York (1978).
Nkurunziza, S. and Ahmed, S.E., Shrinkage Drift Parameter Estimation for Multi-factor Ornstein-Uhlenbeck Processes. Appl. Stoch. Models Bus. Ind. 26 (2010) 103124. Google Scholar
G. Papanicolaou, Diffusion in random media, in Surveys in Applied Mathematics, edited by J.B. Keller, D. McLaughlin and G. Papanicolaou. Plenum Press (1995) 205–255.