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首页> 外文期刊>Journal of Econometrics >On Bayesian Analysis and Computation for Functions with Monotonicity and Curvature Restrictions.
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On Bayesian Analysis and Computation for Functions with Monotonicity and Curvature Restrictions.

机译:关于具有单调性和曲率约束的函数的贝叶斯分析和计算。

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摘要

Our goal is inference for shape-restricted functions. Our functional form consists of finite linear combinations of basis functions. Prior elicitation is difficult due to the irregular shape of the parameter space. We show how to elicit priors that are flexible, theoretically consistent, and proper. We demonstrate that uniform priors over coefficients imply priors over economically relevant quantities that are quite informative and give an example of a non-uniform prior that addresses this issue. We introduce simulation methods that meet challenges posed by the shape of the parameter space. We analyze data from a consumer demand experiment.
机译:我们的目标是推断形状受限制的功能。我们的函数形式由基本函数的有限线性组合组成。由于参数空间的形状不规则,因此事先引发困难。我们展示了如何得出灵活,理论上一致且适当的先验。我们证明,统一的先验高于系数意味着优先于经济上相关的数量,这是非常有用的,并给出了解决这一问题的不均匀先验的示例。我们介绍了模拟方法,这些方法可以应对参数空间形状带来的挑战。我们分析来自消费者需求实验的数据。

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