Optimal Experimental Designs in Regression: A Bootstrap Approach
作者： J. P. Vila
DOI: 10.1007/978-3-642-48678-4_32
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摘要: This paper presents a new family of optimal design criteria for parameter estimation in nonlinear regression, based on minimization expected volumes of, at least second-order correct, bootstrap confidence regions.
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