Optimal Robust Designs: Linear Regression in $R^k$
نویسندگان
چکیده
منابع مشابه
Robust designs for approximately linear regression: M-estimated parameters
We obtain designs, to be used for investigations of response surfaces by regression techniques, when (i) the fitted, linear (in the parameters) response is incorrect and (ii) the parameters are to be estimated robustly. Minimax designs are determined for ‘small’ departures from the fitted response. We specialize to the case in which the experimenter fits a plane, when in fact the true response ...
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One of the factors affecting the statistical analysis of the data is the presence of outliers. The methods which are not affected by the outliers are called robust methods. Robust regression methods are robust estimation methods of regression model parameters in the presence of outliers. Besides outliers, the linear dependency of regressor variables, which is called multicollinearity...
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Fuzzy regression discontinuity (RD) design and instrumental variable(s) (IV) regression share similar identification strategies and numerically yield the same results under certain conditions. While the weak identification problem is widely recognized in IV regressions, it has drawn much less attention in fuzzy RD designs, where the standard t-test can also suffer from asymptotic size distortio...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 1982
ISSN: 0090-5364
DOI: 10.1214/aos/1176345792