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Locally D-optimal designs for a wider class of non-linear models on the k-dimensional ball

with applications to logit and probit models

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A Publisher Correction to this article was published on 12 September 2019

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Abstract

In this paper we extend the results of Radloff and Schwabe (arXiv:1806.00275, 2018), which could be applied for example to Poisson regression, negative binomial regression and proportional hazard models with censoring, to a wider class of non-linear multiple regression models. This includes the binary response models with logit and probit link besides others. For this class of models we derive (locally) D-optimal designs when the design region is a k-dimensional ball. For the corresponding construction we make use of the concept of invariance and equivariance in the context of optimal designs as in our previous paper. In contrast to the former results the designs will not necessarily be exact designs in all cases. Instead approximate designs can appear. These results can be generalized to arbitrary ellipsoidal design regions.

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Change history

  • 12 September 2019

    Unfortunately, due to a technical error, the articles published in issues 60:2 and 60:3 received incorrect pagination. Please find here the corrected Tables of Contents. We apologize to the authors of the articles and the readers.

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Correspondence to Martin Radloff.

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Radloff, M., Schwabe, R. Locally D-optimal designs for a wider class of non-linear models on the k-dimensional ball. Stat Papers 60, 515–527 (2019). https://doi.org/10.1007/s00362-018-01078-4

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  • DOI: https://doi.org/10.1007/s00362-018-01078-4

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