Volume 18, Issue 2 (12-2019)                   JIRSS 2019, 18(2): 173-197 | Back to browse issues page

DOI: 10.29252/jirss.18.2.173

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Department of Statistics, Faculty of Mathematical Sciences, Shahrood University of Technology, Iran , m_arashi_stat@yahoo.com
Abstract:   (860 Views)
In the present article, we develop the well-known preliminary test and Stein-type estimators for the probability density function under association. In this respect, we derive the asymptotic characteristics of the proposed estimators under a set of local alternatives. Some numerical studies are provided for supporting the findings. The result of this article improves the kernel estimate of the marginal probability density function of a strictly stationary sequence of associated random variables. For practical sake, the behavior of the proposed estimators is also analyzed using a real data set.
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Type of Study: Original Paper | Subject: 62Gxx: Nonparametric inference
Received: 2018/09/18 | Accepted: 2019/05/24 | Published: 2019/10/26