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摘要翻译：
在具有当前状态观测的区间删失模型中，变量是个体在观测区间上存在的指标和协变量。当几个个体共享相同的观察间隔时，一个简单的过程以封闭的形式提供了观察时间及其强度分布的新估计量。对于分段常数协变量，它们是$n^{1/2}$-一致的。给出了样本容量的估计量，并对连续区间上的观测独立性和连续类间的观测独立性给出了渐近的$chi^2$检验。
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英文标题：
《Inference in nonparametric current status models with covariates》
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作者：
Odile Pons
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最新提交年份：
2007
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分类信息：
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：
In interval censored models with current status observations, the variables are indicators of the presence of individuals on observation intervals and covariates. When several individuals share the same observation interval, a simple procedure provides new estimators for the distribution of the observation times and their intensity, in a closed form. They are $n^{1/2}$-consistent for piece-wise constant covariates. Estimators of the sample-sizes are deduced and asymptotic $\chi^2$ tests for independence of the observations on consecutive intervals and for independence between consecutive classes for the observed individuals are proposed.
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PDF链接：
https://arxiv.org/pdf/710.169
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