一阶自回归过程的两阶段过程及其与纯顺序过程的比较

IF 0.6 4区数学 Q4 STATISTICS & PROBABILITY Sequential Analysis-Design Methods and Applications Pub Date : 2022-01-06 DOI:10.1080/07474946.2021.2010404

Soudabe Sajjadipanah, E. Mahmoudi, Mohammadsadegh Zamani

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引用次数: 0

摘要

研究了基于最小二乘估计的一阶自回归模型ðARð1ÞÞ的点估计和区间估计问题。结果表明，两阶段方法与最佳固定样本量方法同样有效。在这方面，建立了该过程的重要性质，如渐近风险效率、渐近效率和渐近一致性。通过蒙特卡罗仿真研究，比较了两阶段过程和纯顺序过程的性能。最后，以实时序列数据为例，说明了两阶段方法的适用性。文章历史2020年5月6日收稿2021年6月14日修订2021年9月5日接受

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Two-stage procedure in a first-order autoregressive process and comparison with a purely sequential procedure

A two-stage procedure in a first-order autoregressive model ðARð1ÞÞ is considered that investigates the point and the interval estimation of parameters based on the least squares estimator. The two-stage procedure is shown to be as effective as the best fixed-sample-size procedure. In this regard, the significant properties of the procedure, such as asymptotic risk efficiency, asymptotic efficiency, and asymptotic consistency, are established. A Monte Carlo simulation study is conducted to compare the performance of the two-stage procedure and the purely sequential procedure. Finally, real-time series data are considered to illustrate the applicability of the two-stage procedure. ARTICLE HISTORY Received 6 May 2020 Revised 14 June 2021 Accepted 5 September 2021

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来源期刊

Sequential Analysis-Design Methods and Applications STATISTICS & PROBABILITY-

CiteScore

1.40

自引率

12.50%

发文量

期刊介绍： The purpose of Sequential Analysis is to contribute to theoretical and applied aspects of sequential methodologies in all areas of statistical science. Published papers highlight the development of new and important sequential approaches. Interdisciplinary articles that emphasize the methodology of practical value to applied researchers and statistical consultants are highly encouraged. Papers that cover contemporary areas of applications including animal abundance, bioequivalence, communication science, computer simulations, data mining, directional data, disease mapping, environmental sampling, genome, imaging, microarrays, networking, parallel processing, pest management, sonar detection, spatial statistics, tracking, and engineering are deemed especially important. Of particular value are expository review articles that critically synthesize broad-based statistical issues. Papers on case-studies are also considered. All papers are refereed.