双删失数据的非参数统计推断方法及其应用

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Asamh S. M. Al Luhayb
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引用次数: 0

摘要

本文介绍了在数据同时包含右删失观测值和左删失观测值的情况下进行预测的新的非参数统计方法。这些方法可被视为希尔的 A ( n ) {A}_{\left(n)} 假设的新版本。根据每种版本,我们都得出了预测一个未来观测值 X n + 1 {X}_{n+1} 的生存函数的两个边界,并通过两个例子对这些边界进行了比较。基于所提出的方法,有两个有趣的特点。第一个特点是通过详细的图表展示了左右剔除的影响。第二个特点是可以导出下生存函数和上生存函数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nonparametric methods of statistical inference for double-censored data with applications
This article introduces new nonparametric statistical methods for prediction in case of data containing right-censored observations and left-censored observations simultaneously. The methods can be considered as new versions of Hill’s A ( n ) {A}_{\left(n)} assumption for double-censored data. Two bounds are derived to predict the survival function for one future observation X n + 1 {X}_{n+1} based on each version, and these bounds are compared through two examples. Two interesting features are provided based on the proposed methods. The first one is the detailed graphical presentation of the effects of right and left censoring. The second feature is that the lower and upper survival functions can be derived.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
期刊介绍: ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.
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