随机审查条件下单函数指数模型条件分位数估计的强一致性率

IF 0.6 Q4 STATISTICS & PROBABILITY
Nadia Kadiri, A. Rabhi, A. Bouchentouf
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引用次数: 4

摘要

摘要本文的主要目的是当样本被视为混合序列时,非参数估计审查模型中条件分布的分位数。首先,介绍了条件累积分布函数(cond-cdf)的核型估计器。然后,我们通过反转这个估计的第二cdf来估计分位数,并说明当观测与单指标结构相联系时的渐近性质。建立了该模型核估计的逐点几乎完全收敛性和一致几乎完全收敛(带速率)。这种方法可以应用于时间序列分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Strong uniform consistency rates of conditional quantile estimation in the single functional index model under random censorship
Abstract The main objective of this paper is to non-parametrically estimate the quantiles of a conditional distribution in the censorship model when the sample is considered as an -mixing sequence. First of all, a kernel type estimator for the conditional cumulative distribution function (cond-cdf) is introduced. Afterwards, we estimate the quantiles by inverting this estimated cond-cdf and state the asymptotic properties when the observations are linked with a single-index structure. The pointwise almost complete convergence and the uniform almost complete convergence (with rate) of the kernel estimate of this model are established. This approach can be applied in time series analysis.
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来源期刊
Dependence Modeling
Dependence Modeling STATISTICS & PROBABILITY-
CiteScore
1.00
自引率
0.00%
发文量
18
审稿时长
12 weeks
期刊介绍: The journal Dependence Modeling aims at providing a medium for exchanging results and ideas in the area of multivariate dependence modeling. It is an open access fully peer-reviewed journal providing the readers with free, instant, and permanent access to all content worldwide. Dependence Modeling is listed by Web of Science (Emerging Sources Citation Index), Scopus, MathSciNet and Zentralblatt Math. The journal presents different types of articles: -"Research Articles" on fundamental theoretical aspects, as well as on significant applications in science, engineering, economics, finance, insurance and other fields. -"Review Articles" which present the existing literature on the specific topic from new perspectives. -"Interview articles" limited to two papers per year, covering interviews with milestone personalities in the field of Dependence Modeling. The journal topics include (but are not limited to):  -Copula methods -Multivariate distributions -Estimation and goodness-of-fit tests -Measures of association -Quantitative risk management -Risk measures and stochastic orders -Time series -Environmental sciences -Computational methods and software -Extreme-value theory -Limit laws -Mass Transportations
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