Arbeitspapier
A note on all-bias designs with applications in spline regression models
If a model is fitted to empirical data, bias can arise from terms which are not incorporated in the model assumptions. As a consequence the commonly used optimality criteria based on the generalized variance of the estimate of the model parameters may not lead to efficient designs for the statistical analysis. In this note some general aspects of all-bias designs are presented, which were introduced in this context by Box and Draper (1959). We establish sufficient conditions such that a given design is an all-bias design and illustrate these in the special case of spline regression models. In particular our results generalize recent findings of Woods and Lewis (2006).
- Language
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Englisch
- Bibliographic citation
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Series: Technical Report ; No. 2008,19
- Subject
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all-bias design
spline regression models
robust designs
quadrature formulas
- Event
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Geistige Schöpfung
- (who)
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Dette, Holger
Melas, Viatcheslav B.
- Event
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Veröffentlichung
- (who)
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Technische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (where)
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Dortmund
- (when)
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2008
- Handle
- Last update
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10.03.2025, 11:42 AM CET
Data provider
This object is provided by:
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Dette, Holger
- Melas, Viatcheslav B.
- Technische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Time of origin
- 2008
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