对 "基于运行规则方案的用于监测有限视界过程的改进型霍特林 T2 图表 "的勘误：马尔可夫链方法"

IF 1.3 4区数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Applied Stochastic Models in Business and Industry Pub Date : 2023-12-12 DOI:10.1002/asmb.2833

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引用次数: 0

摘要

本文更正如下：在Chew等人的这篇研究论文1第590页中，致谢中的资助信息有误。正确的资助信息应该是：这项工作由马来西亚高等教育部基础研究资助计划[资助编号：FRGS/1/2019/STG06/USM/02/5]资助，项目名称为 "无限和有限地平线过程中变异系数的新鲁棒性自适应模型"。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Erratum to “An improved Hotelling's T2 chart for monitoring a finite horizon process based on run rules schemes: A Markov-chain approach”

This article corrects the following:

In this research paper by Chew et al.,¹ on page 590, the funding information in the Acknowledgement is incorrect.

The correct funding information should be:

This work is funded by the Ministry of Higher Education Malaysia, Fundamental Research Grant Scheme [Grant Number: FRGS/1/2019/STG06/USM/02/5], for the project entitled “New Robust Adaptive Model for Coefficient of Variation in Infinite and Finite Horizon Processes.”

We apologise for this error.

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来源期刊

Applied Stochastic Models in Business and Industry 数学-数学跨学科应用

CiteScore

2.70

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production. In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (www.isbis.org). The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so. Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process. The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems). The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life. State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.