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Efficiency and Robustness of Least Squares Estimators
K. C. Chanda
Sankhyā: The Indian Journal of Statistics, Series B (1960-2002)
Vol. 38, No. 2 (May, 1976), pp. 153-163
Published by: Indian Statistical Institute
Stable URL: http://www.jstor.org/stable/25052005
Page Count: 11
You can always find the topics here!Topics: Least squares, Estimators, Linear regression, Statistics, Statistical estimation, Mathematical procedures, Regression analysis, Maximum likelihood estimators, Mathematical independent variables, Random variables
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Large sample efficiency of least squares estimation of parameters in a regression set up-linear or nonlinear is explored theoretically. Several cases of heavy, medium, and lean tailed distributions of the regression residuals are investigated numerically. The conclusion is consistent with the classical knowledge that the more heavy tailed or skewed the distribution of the residuals is, the less efficient are the least squares estimators.
Sankhyā: The Indian Journal of Statistics, Series B (1960-2002) © 1976 Indian Statistical Institute