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  • Search: subject:"Design algorithm"
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Year of publication
Subject
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Design algorithm 3 Chemical kinetics 2 Correlated errors 2 D-optimum design 2 Nonlinear models 2 Parameter sensitivities 2 Approximate design 1 Optimum design 1 Support points 1
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Undetermined 3
Type of publication
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Article 3
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Undetermined 3
Author
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Atkinson, Anthony 2 Ucinski, Dariusz 2 Pronzato, Luc 1
Published in...
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Studies in Nonlinear Dynamics & Econometrics 2 Statistics & Probability Letters 1
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RePEc 3
Showing 1 - 3 of 3
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A delimitation of the support of optimal designs for Kiefer’s ϕp-class of criteria
Pronzato, Luc - In: Statistics & Probability Letters 83 (2013) 12, pp. 2721-2728
The paper extends the result of Harman and Pronzato [Harman, R., Pronzato, L., 2007. Improvements on removing non-optimal support points in D-optimum design algorithms. Statistics & Probability Letters 77, 90–94], which corresponds to p=0, to all strictly concave criteria in Kiefer’s...
Persistent link: https://www.econbiz.de/10011040155
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Experimental Design for Time-Dependent Models with Correlated Observations
Ucinski, Dariusz; Atkinson, Anthony - In: Studies in Nonlinear Dynamics & Econometrics 8 (2007) 2, pp. 1217-1217
We describe an algorithm for the construction of optimum experimental designs for the parameters in a regression model when the errors have a correlation structure. Our example is drawn from chemical kinetics, so that the model is nonlinear. Our algorithm has been implemented to be used when the...
Persistent link: https://www.econbiz.de/10004966153
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Cover Image
Experimental Design for Time-Dependent Models with Correlated Observations
Ucinski, Dariusz; Atkinson, Anthony - In: Studies in Nonlinear Dynamics & Econometrics 8 (2004) 2, pp. 1217-1217
We describe an algorithm for the construction of optimum experimental designs for the parameters in a regression model when the errors have a correlation structure. Our example is drawn from chemical kinetics, so that the model is nonlinear. Our algorithm has been implemented to be used when the...
Persistent link: https://www.econbiz.de/10005246304
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