Locally and maximin optimal designs for multi-factor nonlinear models
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Publication:3462144
DOI10.1080/02331888.2014.922562zbMath1336.62210OpenAlexW2075211605WikidataQ57529019 ScholiaQ57529019MaRDI QIDQ3462144
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Publication date: 4 January 2016
Published in: Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331888.2014.922562
additive modelsnonlinear regression modelslocally \(D\)-optimal designsstandardized maximin \(D\)-optimal designs
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Cites Work
- Mixtures of truncated basis functions
- D-optimum designs in multi-factor models with heteroscedastic errors
- Robust experiment design via stochastic approximation
- Optimal designs for a class of polynomials of odd or even degree
- General equivalence theory for optimum designs (approximate theory)
- \(G\)-optimal designs for multi-factor experiments with heteroscedastic errors
- Design optimality in multi-factor generalized linear models in the presence of an unrestricted quantitative factor
- Maximin efficient design of experiment for exponential regression models
- Optimal design for additive partially nonlinear models
