Rao, Calyampudi R. ; Wu, YueHua (2009) A note on constrained M-estimation and its recursive analog in multivariate linear regression models Science in China Series A: Mathematics, 52 (6). pp. 1235-1250. ISSN 1001-6511
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Official URL: http://www.springerlink.com/content/h8m3437524x43u...
Related URL: http://dx.doi.org/10.1007/s11425-009-0084-9
Abstract
In this paper, the constrained M-estimation of the regression coefficients and scatter parameters in a general multivariate linear regression model is considered. Since the 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. In addition, the asymptotic normality of the recursive constrained M-estimators of regression coefficients is established. A Monte Carlo simulation study of the recursion estimates is also provided. Besides, robustness and asymptotic behavior of constrained M-estimators are briefly discussed.
| Item Type: | Article |
|---|---|
| Source: | Copyright of this article belongs to Science in China Press (SCP). |
| Keywords: | Asymptotic Normality; Breakdown Point; Consistency; Constrained M-estimation; Influence Function; Linear Model; M-estimation; Recursion Estimation; Robust Estimation |
| ID Code: | 71917 |
| Deposited On: | 28 Nov 2011 04:23 |
| Last Modified: | 28 Nov 2011 04:23 |
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