Estimations and Optimal Tests in Some Parametric Models

S. Bouzebda, Tewfik Lounis
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引用次数: 1

Abstract

In the present paper, we introduce an efficient method for the estimation in the multidimensional case. The key idea is based on a good assessment of the error without using confidence intervals. The consistency of the proposed estimate is established. Consequently, we discuss the estimation in statistical tests corresponding to parametric context, and prove that this kind of estimators ensures the optimality of statistical tests. We partially extend the scope of our study to some processes. In order to examine the performance of our methodology, finite sample results are performed. This work completes and extends in nontrivial way the results obtained by Lounis (2017).
一些参数模型的估计和最优检验
本文介绍了一种有效的多维情况下的估计方法。关键思想是在不使用置信区间的情况下对误差进行良好的评估。建立了所提估计的一致性。因此,我们讨论了对应于参数上下文的统计检验中的估计,并证明了这类估计保证了统计检验的最优性。我们部分地将我们的研究范围扩展到一些过程。为了检验我们的方法的性能,执行有限样本结果。这项工作以非平凡的方式完成并扩展了Lounis(2017)的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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