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Monotony relations between distribution functions and their application to experimental design
Author:
Wolfgang N
ther a
ther a
| Affiliation: | a Sektion Mathematik, Bergakademie Freiberg, Freiberg |
DOI:
10.1080/02331887908801466
Publication Frequency:
6 issues per year
Subjects:
Mathematical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Formats available:
PDF
(English)
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Abstract
In a linear regression model an estimator of the unknown coefficients is considered which, in special cases, includes the least squares estimator. In the ease of stable symmetric error distribution and by means of a certain monotony relation between distribution functions optimality of this estimator is proved and the designing problem is investigated. A robustness property of optimal designs against the designing criterion and some conclusions are given concerning the least squares estimator in the case of G- and C-optimality.
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| Keywords: Linear regression model; experimental design; robustness of optimal designs against the chosen criterion; monotony relations between distribution functions |
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