By Luc Pronzato
Design of Experiments in Nonlinear types: Asymptotic Normality, Optimality standards and Small-Sample Properties presents a comprehensive coverage of a number of the points of experimental layout for nonlinear versions. The booklet comprises unique contributions to the idea of optimum experiments that would curiosity scholars and researchers within the box. Practitionners encouraged by way of purposes will locate helpful instruments to assist them designing their experiments.
The first 3 chapters reveal the connections among the asymptotic homes of estimators in parametric types and experimental layout, with extra emphasis than traditional on a few specific features just like the estimation of a nonlinear functionality of the version parameters, models with heteroscedastic error, and so on. Classical optimality criteria based on these asymptotic houses are then awarded completely in a different chapter.
Three chapters are devoted to specific issues raised through nonlinear types. the development of design criteria derived from non-asymptotic issues (small-sample state of affairs) is special. the relationship among layout and identifiability/estimability concerns is investigated. numerous techniques are offered to stand the matter attributable to the dependence of an optimum layout at the worth of the parameters to be estimated.
A survey of algorithmic tools for the development of optimum designs is provided.
Read Online or Download Design of Experiments in Nonlinear Models: Asymptotic Normality, Optimality Criteria and Small-Sample Properties (Lecture Notes in Statistics) (Volume 212) PDF
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Extra resources for Design of Experiments in Nonlinear Models: Asymptotic Normality, Optimality Criteria and Small-Sample Properties (Lecture Notes in Statistics) (Volume 212)