Woods, D. C.
Designs for generalized linear models under model uncertainty
At International Conference on Design of Experiments.
13 - 15 May 2005.
Full text not available from this repository.
Standard factorial designs may sometimes be inadequate for
experiments that aim to estimate a generalized linear model, for
example, for describing a binary response in terms of several
variables. A method is proposed for finding designs for such
experiments which uses a criterion that allows for uncertainty in
the link function, the linear predictor or the model parameters,
together with a design search. Designs are assessed and compared
by simulation of the distribution of efficiencies relative to
locally optimal designs over a space of possible models. Designs are
investigated for practical applications and their advantages
Conference or Workshop Item
|Venue - Dates:
||International Conference on Design of Experiments, 2005-05-13 - 2005-05-15
|15 May 2005||Published|
||06 Jun 2005
||16 Apr 2017 23:26
|Further Information:||Google Scholar|
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