摘要翻译：
Birnbaum-Saunders分布，也称为疲劳寿命分布，是可靠性研究中经常使用的分布。我们得到了对Birnbaum-Saunders轮廓似然函数的调整。对形状参数和尺度参数都给出了修正的似然函数，即把形状参数看作是感兴趣的，把尺度参数看作是讨厌的，然后考虑了在形状参数讨厌进入建模的情况下，对尺度参数进行推理是感兴趣的。修正的轮廓极大似然估计是通过最大化相应的调整似然函数得到的。我们给出了不同估计量的有限样本行为的数值证据和相关的似然比检验。结果支持我们提出的调整估计量和检验。本文得到的轮廓似然调整的一个新的方面是它们产生了改进的点估计量和检验。两种轮廓似然调整在对形状参数进行推断时效果良好，其中一种在对尺度参数进行假设检验推断时表现出更好的性能。简要介绍了两个经验应用。
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英文标题：
《On Birnbaum-Saunders Inference》
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作者：
Audrey H.M.A. Cysneiros, Francisco Cribari-Neto, Carlos A.G. Araujo Jr
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最新提交年份：
2008
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分类信息：

一级分类：Statistics        统计学
二级分类：Methodology        方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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一级分类：Mathematics        数学
二级分类：Statistics Theory        统计理论
分类描述：Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计：例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
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一级分类：Statistics        统计学
二级分类：Statistics Theory        统计理论
分类描述：stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近，贝叶斯推论，决策理论，估计，基础，推论，检验。
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英文摘要：
  The Birnbaum-Saunders distribution, also known as the fatigue-life distribution, is frequently used in reliability studies. We obtain adjustments to the Birnbaum--Saunders profile likelihood function. The modified versions of the likelihood function were obtained for both the shape and scale parameters, i.e., we take the shape parameter to be of interest and the scale parameter to be of nuisance, and then consider the situation in which the interest lies in performing inference on the scale parameter with the shape parameter entering the modeling in nuisance fashion. Modified profile maximum likelihood estimators are obtained by maximizing the corresponding adjusted likelihood functions. We present numerical evidence on the finite sample behavior of the different estimators and associated likelihood ratio tests. The results favor the adjusted estimators and tests we propose. A novel aspect of the profile likelihood adjustments obtained in this paper is that they yield improved point estimators and tests. The two profile likelihood adjustments work well when inference is made on the shape parameter, and one of them displays superior behavior when it comes to performing hypothesis testing inference on the scale parameter. Two empirical applications are briefly presented.
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PDF链接：
https://arxiv.org/pdf/709.2943