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Science in China Series A-Mathematics 2009, 52(6) 1235-1250 DOI:
10.1007/s11425-009-0084-9 ISSN: 1006-9283 CN: 11-1787/N |
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| Speciail Issue in Honor of the 65th Birthday of Professor Zhidong Bai |
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A note on constrained M-estimation and its recursive analog in multivariate linear regression models |
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RAO Calyampudi R1 & WU YueHua2 |
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1 Advanced Institute of Mathematics, Statistics and Computer Science, University of Hyderabad, Hyderabad, Andhra Pradesh, India 2 Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, Ontario M3J 1P3, Canada |
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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. |
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Keywords：
asymptotic normality
breakdown point
consistency
constrained M-estimation
influence function
linear model
M-estimation
recursion estimation
robust estimation
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Received 2008-10-23 Revised 2009-04-22 Online: |
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DOI: 10.1007/s11425-009-0084-9 |
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Fund: The research was supported by the Natural Sciences and Engineering Research Council of Canada |
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Corresponding Authors: WU YueHua |
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Email: wuyh@mathstat.yorku.ca |
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About author: |
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