Optimal Design: An Introduction to the Theory for Parameter Estimation
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Dordrecht
Springer Netherlands
1980
|
| Schriftenreihe: | Monographs on Applied Probability and Statistics
1 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Prior to the 1970's a substantial literature had accumulated on the theory of optimal design, particularly of optimal linear regression design. To a certain extent the study of the subject had been piecemeal, different criteria of optimality having been studied separately. Also to a certain extent the topic was regarded as being largely of theoretical interest and as having little value for the practising statistician. However during this decade two significant developments occurred. It was observed that the various different optimality criteria had several mathematical properties in common; and general algorithms for constructing optimal design measures were developed. From the first of these there emerged a general theory of remarkable simplicity and the second at least raised the possibility that the theory would have more practical value. With respect to the second point there does remain a limiting factor as far as designs that are optimal for parameter estimation are concerned, and this is that the theory assumes that the model be collected is known a priori. This of course underlying data to is seldom the case in practice and it often happens that designs which are optimal for parameter estimation allow no possibility of model validation. For this reason the theory of design for parameter estimation may well have to be combined with a theory of model validation before its practical potential is fully realized. Nevertheless discussion in this monograph is limited to the theory of design optimal for parameter estimation |
| Beschreibung: | 1 Online-Ressource (VIII, 86 p) |
| ISBN: | 9789400959125 9789400959149 |
| DOI: | 10.1007/978-94-009-5912-5 |
Internformat
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Datensatz im Suchindex
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| discipline | Allgemeine Naturwissenschaft Physik |
| doi_str_mv | 10.1007/978-94-009-5912-5 |
| format | Electronic eBook |
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| isbn | 9789400959125 9789400959149 |
| language | English |
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| spelling | Silvey, Samuel David Verfasser aut Optimal Design An Introduction to the Theory for Parameter Estimation by Samuel David Silvey Dordrecht Springer Netherlands 1980 1 Online-Ressource (VIII, 86 p) txt rdacontent c rdamedia cr rdacarrier Monographs on Applied Probability and Statistics 1 Prior to the 1970's a substantial literature had accumulated on the theory of optimal design, particularly of optimal linear regression design. To a certain extent the study of the subject had been piecemeal, different criteria of optimality having been studied separately. Also to a certain extent the topic was regarded as being largely of theoretical interest and as having little value for the practising statistician. However during this decade two significant developments occurred. It was observed that the various different optimality criteria had several mathematical properties in common; and general algorithms for constructing optimal design measures were developed. From the first of these there emerged a general theory of remarkable simplicity and the second at least raised the possibility that the theory would have more practical value. With respect to the second point there does remain a limiting factor as far as designs that are optimal for parameter estimation are concerned, and this is that the theory assumes that the model be collected is known a priori. This of course underlying data to is seldom the case in practice and it often happens that designs which are optimal for parameter estimation allow no possibility of model validation. For this reason the theory of design for parameter estimation may well have to be combined with a theory of model validation before its practical potential is fully realized. Nevertheless discussion in this monograph is limited to the theory of design optimal for parameter estimation Science (General) Science, general Naturwissenschaft Regressionsanalyse (DE-588)4129903-6 gnd rswk-swf Lineare Regression (DE-588)4167709-2 gnd rswk-swf Regressionsanalyse (DE-588)4129903-6 s 1\p DE-604 Lineare Regression (DE-588)4167709-2 s 2\p DE-604 https://doi.org/10.1007/978-94-009-5912-5 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Silvey, Samuel David Optimal Design An Introduction to the Theory for Parameter Estimation Science (General) Science, general Naturwissenschaft Regressionsanalyse (DE-588)4129903-6 gnd Lineare Regression (DE-588)4167709-2 gnd |
| subject_GND | (DE-588)4129903-6 (DE-588)4167709-2 |
| title | Optimal Design An Introduction to the Theory for Parameter Estimation |
| title_auth | Optimal Design An Introduction to the Theory for Parameter Estimation |
| title_exact_search | Optimal Design An Introduction to the Theory for Parameter Estimation |
| title_full | Optimal Design An Introduction to the Theory for Parameter Estimation by Samuel David Silvey |
| title_fullStr | Optimal Design An Introduction to the Theory for Parameter Estimation by Samuel David Silvey |
| title_full_unstemmed | Optimal Design An Introduction to the Theory for Parameter Estimation by Samuel David Silvey |
| title_short | Optimal Design |
| title_sort | optimal design an introduction to the theory for parameter estimation |
| title_sub | An Introduction to the Theory for Parameter Estimation |
| topic | Science (General) Science, general Naturwissenschaft Regressionsanalyse (DE-588)4129903-6 gnd Lineare Regression (DE-588)4167709-2 gnd |
| topic_facet | Science (General) Science, general Naturwissenschaft Regressionsanalyse Lineare Regression |
| url | https://doi.org/10.1007/978-94-009-5912-5 |
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