加速破坏性降解测试数据的非线性量值回归

IF 2 3区工程技术 Q3 ENGINEERING, INDUSTRIAL

IISE Transactions Pub Date : 2024-05-03 DOI:10.1080/24725854.2024.2351905

Suk Joo Bae, Munwon Lim

引用次数: 0

摘要

加速破坏性降解试验 (ADDT) 数据的传统回归方法将平均曲线建模为代表性曲线。然而，平均值模式的最大似然估计值 (MLEs) 并不可靠。

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

A Nonlinear Quantile Regression for Accelerated Destructive Degradation Testing Data

Traditional regression approaches to accelerated destructive degradation test (ADDT) data have modeled the mean curve as representative. However, maximum likelihood estimates (MLEs) of the mean mod...

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

IISE Transactions Engineering-Industrial and Manufacturing Engineering

CiteScore

5.70

自引率

7.70%

发文量

期刊介绍： IISE Transactions is currently abstracted/indexed in the following services: CSA/ASCE Civil Engineering Abstracts; CSA-Computer & Information Systems Abstracts; CSA-Corrosion Abstracts; CSA-Electronics & Communications Abstracts; CSA-Engineered Materials Abstracts; CSA-Materials Research Database with METADEX; CSA-Mechanical & Transportation Engineering Abstracts; CSA-Solid State & Superconductivity Abstracts; INSPEC Information Services and Science Citation Index. Institute of Industrial and Systems Engineers and our publisher Taylor & Francis make every effort to ensure the accuracy of all the information (the "Content") contained in our publications. However, Institute of Industrial and Systems Engineers and our publisher Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Institute of Industrial and Systems Engineers and our publisher Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Institute of Industrial and Systems Engineers and our publisher Taylor & Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to, or arising out of the use of the Content. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions .