Some Properties of a Recursive Procedure for High Dimensional Parameter Estimation in Linear Model with Regularization
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Author(s)
Theoretical results related to properties of a
regularized recursive algorithm for estimation of a high dimensional
vector of parameters are presented and proved. The recursive character
of the procedure is proposed to overcome the difficulties with high
dimension of the observation vector in computation of a statistical
regularized estimator. As to deal with high dimension of the vector of
unknown parameters, the regularization is introduced by specifying a
priori non-negative covariance structure for the vector of estimated
parameters. Numerical example with Monte-Carlo simulation for a
low-dimensional system as well as the state/parameter estimation in a
very high dimensional oceanic model is presented to demonstrate the
efficiency of the proposed approach.
KEYWORDS
Cite this paper
Hoang, H. and Baraille, R. (2014) Some Properties
of a Recursive Procedure for High Dimensional Parameter Estimation in
Linear Model with Regularization. Open Journal of Statistics, 4, 921-932. doi: 10.4236/ojs.2014.411087.
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