Likelihood-based analysis of doubly-truncated data under the location-scale and AFT model

Achim Dörre, Chung Yan Huang, Yi Kuan Tseng, Takeshi Emura

研究成果: 雜誌貢獻期刊論文同行評審

6 引文 斯高帕斯(Scopus)


Doubly-truncated data arise in many fields, including economics, engineering, medicine, and astronomy. This article develops likelihood-based inference methods for lifetime distributions under the log-location-scale model and the accelerated failure time model based on doubly-truncated data. These parametric models are practically useful, but the methodologies to fit these models to doubly-truncated data are missing. We develop algorithms for obtaining the maximum likelihood estimator under both models, and propose several types of interval estimation methods. Furthermore, we show that the confidence band for the cumulative distribution function has closed-form expressions. We conduct simulations to examine the accuracy of the proposed methods. We illustrate our proposed methods by real data from a field reliability study, called the Equipment-S data.

頁(從 - 到)375-408
期刊Computational Statistics
出版狀態已出版 - 3月 2021


深入研究「Likelihood-based analysis of doubly-truncated data under the location-scale and AFT model」主題。共同形成了獨特的指紋。