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Bayesian local influence analysis: With an application to stochastic frontiers

机译:贝叶斯局部影响分析:在随机前沿中的应用

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A Bayesian alternative to Zhuo (2018) is presented. The method is of general interest as it presents an explicit formula for the local sensitivity of log marginal likelihood when observations vary by a small amount. The remarkable feature is that the formula is very easy to compute and does not require knowledge of the marginal likelihood which is, invariably, extremely difficult to compute. Similar expressions are derived for posterior moments and other functions of interest, including inefficiency. Methods for examining prior sensitivity in a straightforward way are also presented. The methods are illustrated in the context of a stochastic production frontier. (C) 2018 Published by Elsevier B.V.
机译:提出了卓(2018)的贝叶斯替代方法。该方法具有普遍意义,因为当观察值变化很小时,它为对数边际可能性的局部敏感性提供了一个明确的公式。显着的特征是该公式非常易于计算,并且不需要了解边缘概率,而边缘概率总是难于计算。对于后矩和其他感兴趣的功能(包括效率低下),得出了类似的表达式。还提出了以直接方式检查先验敏感性的方法。在随机生产前沿的情况下说明了这些方法。 (C)2018由Elsevier B.V.发布

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