Scholarlink

<p>In this article, we propose a set of accurate direct and synthetic estimators for the small domains mean using auxiliary character under simple random sampling (SRS). The properties such as bias and mean square error (MSE) of the proposed direct and synthetic estimators are obtained and compared with the properties of the existing estimators. A simulation study is done on artificially produced populations to check the accuracy of the proposed estimators viz-a-viz some prominent existing estimators. The comparative study based on MSE and percent relative efficiency (PRE) shows the superiority of the proposed direct and synthetic estimators as compare to the existing direct and synthetic estimators. Furthermore, an application of the proposed estimators is also provided using Sweden municipalities data.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

On accurate direct and synthetic estimators for domain mean with an application to municipalities data

  • 期刊论文

  • 发表日期：

    2025年6月24日

查看全文
  • Shashi Bhushan,
  • Anoop Kumar,
  • Rohini Pokhrel

摘要

In this article, we propose a set of accurate direct and synthetic estimators for the small domains mean using auxiliary character under simple random sampling (SRS). The properties such as bias and mean square error (MSE) of the proposed direct and synthetic estimators are obtained and compared with the properties of the existing estimators. A simulation study is done on artificially produced populations to check the accuracy of the proposed estimators viz-a-viz some prominent existing estimators. The comparative study based on MSE and percent relative efficiency (PRE) shows the superiority of the proposed direct and synthetic estimators as compare to the existing direct and synthetic estimators. Furthermore, an application of the proposed estimators is also provided using Sweden municipalities data.