多元背景下的斯坦因估算

Adrian Fischer, Robert E. Gaunt, Yvik Swan
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引用次数: 0

摘要

我们利用斯坦因特征推导出 i.i.d. 情况下几种多元分布参数的新时刻型估计器;我们还揭示了这些估计器的渐近特性。我们的例子包括多元截断正态分布和几种球形分布。这些估计值是显式的,因此为最大似然估计值提供了一种有趣的替代方法。我们通过竞争性模拟研究评估了这些估计器的质量,并将它们的行为与文献中其他估计器的性能进行了比较。
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Stein estimation in a multivariate setting
We use Stein characterisations to derive new moment-type estimators for the parameters of several multivariate distributions in the i.i.d. case; we also derive the asymptotic properties of these estimators. Our examples include the multivariate truncated normal distribution and several spherical distributions. The estimators are explicit and therefore provide an interesting alternative to the maximum-likelihood estimator. The quality of these estimators is assessed through competitive simulation studies in which we compare their behaviour to the performance of other estimators available in the literature.
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