The effects of adaptation on maximum likelihood inference for nonlinear models with normal errors

DOI10.1016/J.JSPI.2021.02.002zbMath1465.62124OpenAlexW3132407324MaRDI QIDQ830758

Chiara Tommasi, Nancy Flournoy, Caterina May

Publication date: 7 May 2021

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2021.02.002

zbMATH Keywords

nonlinear regressionstable convergenceexponential modelEmax modelGaussian scale mixturestwo-stage adaptive optimal design

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Optimal statistical designs (62K05) General nonlinear regression (62J02)

Related Items (1)

Inference for a two-stage enrichment design

Uses Software

• SAS
• DoseFinding

Cites Work

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• Optimal designs for the emax, log-linear and exponential models
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• Stable Convergence and Stable Limit Theorems
• The Sequential Generation of $D$-Optimum Experimental Designs

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