论文标题
关于增加赔率分布的非参数推断
Nonparametric inference about increasing odds rate distributions
论文作者
论文摘要
为了改善终生分布的非参数估计，我们建议使用增加的几率率（IOR）模型作为其他流行但更具限制性的``不良老化''模型的替代方法，例如危害率的增加。这扩大了某些方法在顺序限制下用于统计推断的适用性范围，因为IOR模型与重尾和浴缸分布兼容。我们研究了IOR约束下感兴趣的累积分布函数的强烈一致的估计器。数值证据表明，当基础模型确实属于IOR家族时，该估计器通常比经典的经验分布函数通常优于经典的经验分布函数。我们还研究了两个不同的测试，旨在检测与IOR财产的偏差，并确定它们的一致性。这些测试的性能还通过模拟进行评估。
To improve nonparametric estimates of lifetime distributions, we propose using the increasing odds rate (IOR) model as an alternative to other popular, but more restrictive, ``adverse ageing'' models, such as the increasing hazard rate one. This extends the scope of applicability of some methods for statistical inference under order restrictions, since the IOR model is compatible with heavy-tailed and bathtub distributions. We study a strongly uniformly consistent estimator of the cumulative distribution function of interest under the IOR constraint. Numerical evidence shows that this estimator often outperforms the classic empirical distribution function when the underlying model does belong to the IOR family. We also study two different tests, aimed at detecting deviations from the IOR property, and we establish their consistency. The performance of these tests is also evaluated through simulations.
