具有单调退化的寿命分析:一种基于均匀伽马过程的改进的首次撞击时间模型。

IF 1.2 3区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Clara Bertinelli Salucci, Azzeddine Bakdi, Ingrid Kristine Glad, Bo Henry Lindqvist, Erik Vanem, Riccardo De Bin
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引用次数: 0

摘要

在时间到事件分析的背景下,首次命中时间方法将事件的发生作为某个演化过程的终点。过程的特征与分析有很大的相关性,这使得这类模型很有趣,特别适合于已知退化路径的应用。在降解只会恶化的情况下,单调过程是最合适的选择。为了考虑退化趋势的单调性,提出了一种基于底层齐次伽马过程的首次命中时间模型的增强算法。该算法的预测能力和通用性通过工程和生物医学应用的实际数据示例以及模拟示例得到了证明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lifetime analysis with monotonic degradation: a boosted first hitting time model based on a homogeneous gamma process.

In the context of time-to-event analysis, First hitting time methods consider the event occurrence as the ending point of some evolving process. The characteristics of the process are of great relevance for the analysis, which makes this class of models interesting and particularly suitable for applications where something about the degradation path is known. In cases where the degradation can only worsen, a monotonic process is the most suitable choice. This paper proposes a boosting algorithm for first hitting time models based on an underlying homogeneous gamma process to account for the monotonicity of the degradation trend. The predictive power and versatility of the algorithm are shown with real data examples from both engineering and biomedical applications, as well as with simulated examples.

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来源期刊
Lifetime Data Analysis
Lifetime Data Analysis 数学-数学跨学科应用
CiteScore
2.30
自引率
7.70%
发文量
43
审稿时长
3 months
期刊介绍: The objective of Lifetime Data Analysis is to advance and promote statistical science in the various applied fields that deal with lifetime data, including: Actuarial Science – Economics – Engineering Sciences – Environmental Sciences – Management Science – Medicine – Operations Research – Public Health – Social and Behavioral Sciences.
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