Shrinkage strategies in some multiple multi-factor dynamical systems
Shrinkage strategies in some multiple multi-factor dynamical systems
复制标题
一些多因素动力系统中的收缩策略
DOI：
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发表时间：
2012
期刊：
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通讯作者：
S. Nkurunziza
中科院分区：
文献类型：
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作者：
S. Nkurunziza
本文研究了m个独立多元扩散过程漂移参数矩阵的估计问题。更具体地说，我们考虑了m-参数矩阵满足某些不确定约束的情况。考虑到这样的不确定性，我们开发了收缩估计，它比最大似然估计(MLE)的性能有所改善。在渐近分布二次风险准则下，我们研究了已建立的估计量的相对优势。此外，我们对中小时间长度的观察期进行了模拟研究，证实了收缩估计器优于最大似然估计的理论发现。该方法对模型评估和变量选择具有一定的参考价值。
In this paper, we are interested in estimation problem for the drift parameters matrices of m independent multivariate diffusion processes. More specifically, we consider the case where the m -parameters matrices are supposed to satisfy some uncertain constraints. Given such an uncertainty, we develop shrinkage estimators which improve over the performance of the maximum likelihood estimator (MLE). Under an asymptotic distributional quadratic risk criterion, we study the relative dominance of the established estimators. Further, we carry out simulation studies for observation periods of small and moderate lengths of time that corroborate the theoretical finding for which shrinkage estimators outperform over the MLE. The proposed method is useful in model assessment and variable selection.