Implementation of the sequential optimal design strategy in Type-II progressive censoring with the GLM-based mechanism

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY
Fatemeh Hassantabar Darzi, Firoozeh Haghighi, Samaneh Eftekhari Mahabadi
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引用次数: 0

Abstract

Single-objective optimal designs might be criticized for not covering all aspects of the experiment when the experiment possesses multiple goals. In such a case, multi-objective optimal design is of interest. This paper adopts a sequential approach to obtain a multi-objective optimal design for Type-II progressive censoring with a dependent GLM-based random removal mechanism. Several simulation studies are conducted to evaluate and compare the performance of the proposed approach. A sensitivity analysis has been performed to investigate the effect of misspecification of design input parameters. Also, the sequential optimal design solution is used to construct the bounds in the \(\epsilon\)-constraint optimal design. Finally, the usefulness of the proposed strategy is demonstrated through two real-life data analyses.

Abstract Image

利用基于 GLM 的机制,在第二类渐进剔除中实施顺序优化设计策略
当实验具有多个目标时,单目标优化设计可能会因无法涵盖实验的所有方面而受到批评。在这种情况下,多目标优化设计就显得尤为重要。本文采用一种序列方法,通过基于依赖 GLM 的随机剔除机制,获得 II 型渐进剔除的多目标最优设计。本文进行了多项模拟研究,以评估和比较所提方法的性能。还进行了敏感性分析,以研究设计输入参数指定错误的影响。同时,利用顺序优化设计方案来构建 \(\epsilon\)- 约束优化设计中的边界。最后,通过两个实际数据分析证明了所提策略的实用性。
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来源期刊
Journal of the Korean Statistical Society
Journal of the Korean Statistical Society 数学-统计学与概率论
CiteScore
1.30
自引率
0.00%
发文量
37
审稿时长
3 months
期刊介绍: The Journal of the Korean Statistical Society publishes research articles that make original contributions to the theory and methodology of statistics and probability. It also welcomes papers on innovative applications of statistical methodology, as well as papers that give an overview of current topic of statistical research with judgements about promising directions for future work. The journal welcomes contributions from all countries.
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