平稳遍历数据右截尾回归模型的非参数m估计

Q Mathematics

Statistical Methodology Pub Date : 2016-12-01 DOI:10.1016/j.stamet.2016.10.002

Mohamed Chaouch , Naâmane Laïb , Elias Ould Saïd

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引用次数: 7

摘要

研究具有平稳遍历数据的右截尾回归模型的非参数m估计。当协变量在Rd (d≥1)中取其值并且数据从平稳遍历过程中采样时，将鲁棒回归族的核型估计量定义为隐函数。在温和的假设条件下，建立了估计量的强相合性和渐近分布。此外，提供了一个可用的置信区间，它不依赖于任何未知量。我们的结果不需要任何混合条件，也不需要存在边际密度。并在模拟数据的基础上进行了对比研究。

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Nonparametric M-estimation for right censored regression model with stationary ergodic data

The present paper deals with a nonparametric $M$ -estimation for right censored regression model with stationary ergodic data. Defined as an implicit function, a kernel-type estimator of a family of robust regression is considered when the covariate takes its values in $R^{d}$ ( $d \geq 1$ ) and the data are sampled from a stationary ergodic process. The strong consistency (with rate) and the asymptotic distribution of the estimator are established under mild assumptions. Moreover, a usable confidence interval is provided which does not depend on any unknown quantity. Our results hold without any mixing condition and do not require the existence of marginal densities. A comparison study based on simulated data is also provided.

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来源期刊

Statistical Methodology STATISTICS & PROBABILITY-

CiteScore

0.59

自引率

0.00%

发文量

期刊介绍： Statistical Methodology aims to publish articles of high quality reflecting the varied facets of contemporary statistical theory as well as of significant applications. In addition to helping to stimulate research, the journal intends to bring about interactions among statisticians and scientists in other disciplines broadly interested in statistical methodology. The journal focuses on traditional areas such as statistical inference, multivariate analysis, design of experiments, sampling theory, regression analysis, re-sampling methods, time series, nonparametric statistics, etc., and also gives special emphasis to established as well as emerging applied areas.