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D-optimal designs for beta regression models with single predictor

机译:具有单一预测变量的Beta回归模型的D最优设计

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The problem of construction of D-optimal designs for beta regression models involving one predictor is considered for the mean-precision parameterization suggested by Ferrari and Cribari-Neto [Beta regression for modelling rates and proportions. J Appl Stat. 2004;31:799-815]. Here we use the logit link function for the mean sub-model. These designs are presented and discussed for unrestricted as well as restricted design regions by considering the precision parameter as (1) a known constant and (2) an unknown constant. Efficiency comparison of obtained designs with commonly used equi-weighted, equi-spaced designs is made to recommend designs for practical use. Real-life applications are given to show the usefulness of these designs.
机译:对于Ferrari和Cribari-Neto建议的平均精度参数化,考虑了涉及一个预测变量的beta回归模型的D最优设计的构造问题[Beta回归模型和比例。 J Appl统计。 2004; 31:799-815]。在这里,我们对均值子模型使用logit链接函数。通过将精度参数视为(1)已知常数和(2)未知常数,针对不受限制和受限制的设计区域介绍和讨论这些设计。将获得的设计与常用的等权重,等距设计进行效率比较,以推荐实用的设计。给出了现实生活中的应用程序,以显示这些设计的实用性。

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