On Constrained M-estimation and Its Recursive Analog in Multivariate Linear Regression Models
نویسندگان
چکیده
In this paper, the constrained M-estimation of the regression coefficients and scatter parameters in a multivariate linear regression model is considered. Robustness and asymptotic behavior are investigated. Since constrained M-estimation is not easy to compute, an up-dating recursion procedure is proposed to simplify the computation of the estimators when a new observation is obtained. We show that, under mild conditions, the recursion estimates are strongly consistent. A Monte Carlo simulation study of the recursion estimates is also provided.
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