Nonparametric Bayesian optimal designs for exponential regression model

Goudarzi Manizheh; Jafari Habib; Khazaei Soleiman

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Nonparametric Bayesian optimal designs for exponential regression model

机译：指数回归模型的非参数贝叶斯最优设计

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摘要

Constructing the Bayesian optimal design depends on the choice of a prior distribution for the unknown parameter. Lacking informative or historical knowledge of the parameter, a parametric Bayesian approach cannot be expected in complex statistical problems. In this regard, a nonparametric Bayesian approach can be used, in which random prior distribution is considered. The Dirichlet process is employed as a prior on the space of distribution functions. In this paper, a non-parametric Bayesian approach is incorporated into an optimal design criterion. This method is illustrated by an example.

机译：构建贝叶斯最佳设计取决于未知参数的先前分配的选择。缺乏对参数的信息或历史知识，在复杂的统计问题中不能预期参数贝叶斯方法。在这方面，可以使用非参数贝叶斯方法，其中考虑随机的先前分布。 Dirichlet工艺作为在分布函数的空间上作为先前的。在本文中，非参数贝叶斯方法被纳入最佳设计标准。该方法通过示例说明。

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来源
《Communications in Statistics》 |2021年第6期|1809-1819|共11页
作者
Goudarzi Manizheh; Jafari Habib; Khazaei Soleiman;
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作者单位

Razi Univ Dept Stat Kermanshah Iran;

Razi Univ Dept Stat Kermanshah Iran;

Razi Univ Dept Stat Kermanshah Iran;

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收录信息美国《科学引文索引》(SCI);
原文格式 PDF
正文语种 eng
中图分类
关键词
Bayesian D-optimal designs; Nonparametric Bayesian; Dirichlet process; Random functionals;

机译：贝叶斯D-最优设计;非参数贝叶斯;Dirichlet Process;随机功能;

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1. Bayesian D-optimal design for logistic regression model with exponential distribution for random intercept [J] . Maram Parisa Parsa, Jafari Habib Journal of statistical computation and simulation . 2016,第10a12期

机译：指数分布随机拦截的逻辑回归模型的贝叶斯D最优设计
2. Bayesian Minimally Supported D-Optimal Designs for an Exponential Regression Model [J] . Zhide Fang, Douglas P. Wiens Communications in Statistics. A, Theory and Methods . 2004,第5期

机译：贝叶斯最小支持的D-Optimal设计用于指数回归模型
3. Bayesian optimal sequential design for nonparametric regression via inhomogeneous evolutionary MCMC [J] . Marco A.R. Ferreira, Nilotpal Sanyal Statistical Methodology . 2014,第may期

机译：通过非均匀进化MCMC进行非参数回归的贝叶斯最优顺序设计
4. Dynamic Bayesian Network and Nonparametric Regression for Nonlinear Modeling of Gene Networks from Time Series Gene Expression Data [C] . SunYong Kim, Seiya Imoto, Satoru Miyano First International Workshop on Computational Methods in Systems Biology CMSB 2003, Feb 24-26, 2003, Rovereto, Italy . 2003

机译：基于时间序列基因表达数据的基因网络非线性建模的动态贝叶斯网络和非参数回归
5. LOF of logistic GEE models and cost efficient Bayesian optimal designs for nonlinear combinations of parameters in nonlinear regression models. [D] . Tang, Zhongwen. 2008

机译：Logistic GEE模型的LOF和具有成本效益的贝叶斯优化设计，用于非线性回归模型中参数的非线性组合。
6. What is the optimal fit-for-purpose design in an oncology first-in-human trial?: 3+3 vs. Bayesian logistic regression model [O] . Sun Young Yum 2020

机译：肿瘤学首次在人体试验中最佳的适应目的设计是什么？：3 + 3 vs贝叶斯逻辑回归模型
7. A Bayesian Nonparametric Causal Model for Regression Discontinuity Designs [O] . Karabatsos, George, Walker, Stephen G. 2015

机译：回归不连续的贝叶斯非参数因果模型设计
8. Construction of Asymptotically Optimal and Independent Nonparametric ExperimentalDesign Tests in the Cox Regression Model and for Distributions with a Location Parameter [R] . Terpstra, T. J. 1990

机译：Cox回归模型中渐近最优且独立的非参数实验设计测试的构造及具有位置参数的分布

Nonparametric Bayesian optimal designs for exponential regression model

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