Bertinelli Salucci Clara, Bakdi Azzeddine, Glad Ingrid Kristine, Lindqvist Bo Henry, Vanem Erik, De Bin Riccardo
Department of Mathematics, University of Oslo, Moltke Moes vei 35, 0851, Oslo, Norway.
Corvus Energy, Tormod Gjestlands veg 51, 3936, Porsgrunn, Norway.
Lifetime Data Anal. 2025 Apr;31(2):300-339. doi: 10.1007/s10985-025-09648-z. Epub 2025 Apr 5.
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.
在生存时间分析的背景下,首次击中时间方法将事件发生视为某个演化过程的终点。该过程的特征对于分析至关重要,这使得这类模型很有趣,并且特别适用于已知某些关于退化路径信息的应用。在退化只会加剧的情况下,单调过程是最合适的选择。本文基于潜在的齐次伽马过程,为首次击中时间模型提出了一种提升算法,以考虑退化趋势的单调性。通过工程和生物医学应用的实际数据示例以及模拟示例,展示了该算法的预测能力和通用性。