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Semiparametric Likelihood-based Inference for censored data with Auxiliary Information from External Massive data Sources

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Acta Mathematicae Applicatae Sinica 2020年第3期36卷 642-656页

作者： Yue-xin FANG Yong ZHOU School of Statistics and Management Shanghai University of Finance and EconomicsShanghai200433China Key Laboratory of Advanced Theory and Application in Statistics and data Science MOEand Academy of Statistics and Interdisciplinary SciencesEast China Normal UniversityShanghai 200062China

Published auxiliary information can be helpful in conducting statistical inference in a new *** this paper,we synthesize the auxiliary information with semiparametric likelihood-based inference for censoring data with the total sample size is *** express the auxiliary information as constraints on the regression coefficients and the covariate distribution,then use empirical likelihood method for general estimating equations to improve the efficiency of the interested parameters in the specified *** consistency and asymptotic normality of the resulting regression parameter estimators *** numerical simulation and application with different supposed conditions show that the proposed method yields a substantial gain in efficiency of the interested parameters.

关键词： Auxiliary information Massive data censored data Empirical likelihood Estimation equations

Kernel Estimators of the ROC Curve with censored data

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Acta Mathematicae Applicatae Sinica 2013年第1期29卷 43-54页

作者： Fang-fang Bai Yong Zhou Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Statistics and Management Shanghai University of Finance and Economics

Receiver operating characteristic （ROC） curves are often used to study the two sample problem in medical studies. However, most data in medical studies are censored. Usually a natural estimator is based on the Kaplan-Meier estimator. In this paper we propose a smoothed estimator based on kernel techniques for the ROC curve with censored data. The large sample properties of the smoothed estimator are established. Moreover, deficiency is considered in order to compare the proposed smoothed estimator of the ROC curve with the empirical one based on Kaplan-Meier estimator. It is shown that the smoothed estimator outperforms the direct empirical estimator based on the Kaplan-Meier estimator under the criterion of deficiency. A simulation study is also conducted and a real data is analyzed.

关键词： ROC curve smoothed estimator censored data Kaplan-Meier estimator deficiency

ESTIMATORS AND SOME BEHAVIORS FORA PARTIALLY LINEAR MODEL WITH censored data

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Acta Mathematica Scientia 1999年第3期19卷 321-331页

作者：陈平 Department of Mathematics Southeast University Nanjing 210096 China

This paper considers the local linear regression estimators for partially linear model with censored data. Which have some nice large-sample behaviors and are easy to implement. By many simulation runs, the author als... 详细信息

关键词： partial linear model censored data local linear smoothing cross-validation kernel estimator

LIMIT THEOREMS FOR INTEGRAL TYPE ESTIMATORS WITH censored data

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Acta Mathematicae Applicatae Sinica 1998年第3期14卷 245-251页

作者：郑祖康 Department of Statistics and Operations Research Fudan University Shanghai China

In survival analysis, the Kaplan-Meter estimator plays a very important role, and its asymptotic properties have been studied by many authors. In recefit years, people find that someimportant statistics can be expressed as the integrals with respect to it. In this paper we shalldiscuss the asymptotic behavior of such integrals. The strong convergence rste shall be givenand the weak convergence result in space D shall be proved.

关键词： censored data Kaplan-Meter estimator

Asymptotic Properties of Wavelet Estimators in a Semiparametric Regression Model with censored data

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Wuhan University Journal of Natural Sciences 2012年第4期17卷 290-296页

作者： HU Hongchang FENG Yuan College of Mathematics and Statistics Hubei NormalUniversity Huangshi 435002 Hubei China School of Mathematics and Statistics Wuhan UniversityWuhan 430072 Hubei China

Consider a semiparametric regression model Y_i=X_iβ＋g（t_i）＋e_i, 1 ≤ i ≤ n, where Y_i is censored on the right by another random variable C_i with known or unknown distribution G. The wavelet estimators of parameter and nonparametric part are given by the wavelet smoothing and the synthetic data methods. Under general conditions, the asymptotic normality for the wavelet estimators and the convergence rates for the wavelet estimators of nonparametric components are investigated. A numerical example is given.

关键词： semiparametric regression model censored data wavelet estimate asymptotic normality convergence rate in probability

Empirical Likelihood Based Variable Selection for Varying Coefficient Partially Linear Models with censored data

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Journal of Mathematical Research with Applications 2013年第4期33卷 493-504页

作者： Peixin ZHAO Department of Mathematics Hechi University

In this paper, we consider the variable selection for the parametric components of varying coefficient partially linear models with censored data. By constructing a penalized auxiliary vector ingeniously, we propose an empirical likelihood based variable selection procedure, and show that it is consistent and satisfies the sparsity. The simulation studies show that the proposed variable selection method is workable.

关键词： varying coefficient partially linear models empirical likelihood censored data variable selection.

Estimation of Semiparametric Model with censored data

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Estimation of Semiparametric Model with Censored Data

Using Extreme Value Theory Approaches to Estimate High Quantiles for Stroke data

2010 Chinese Control and Decision Conference

作者： Chen Zhongwei and Lu Yiqiang Institute of Electronic Technology,the PLA Information Engineering University,Zhengzhou,450004

For semiparametric regression model with censored data,we firstly propose the estimators of parametric and nonparametric part by the use of kernel method based on distribution function and least squares ***,the asympt... 详细信息

关键词： semiparametric model censored data asymptotic normality strong consistency

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Open Journal of Statistics 2024年第1期14卷 150-162页

作者： Justin Ushize Rutikanga Aliou Diop Charline Uwilingiyimana African Institute of Mathematical Sciences Rwandan Center Kigali Rwanda College of Agriculture Animal Sciences and Veterinary Medicine (CAVM) University of Rwanda Musanze Rwanda LERSTAD Gaston Berger University Saint Louis Senegal Department of Statistics Applied to Economy INES Ruhengeri Institute of Applied Sciences Musanze Rwanda

This paper aims to explore the application of Extreme Value Theory (EVT) in estimating the conditional extreme quantile for time-to-event outcomes by examining the functional relationship between ambulatory blood pressure trajectories and clinical outcomes in stroke patients. The study utilizes EVT to analyze the functional connection between ambulatory blood pressure trajectories and clinical outcomes in a sample of 297 stroke patients. The 24-hour ambulatory blood pressure measurement curves for every 15 minutes are considered, acknowledging a censored rate of 40%. The findings reveal that the sample mean excess function exhibits a positive gradient above a specific threshold, confirming the heavy-tailed distribution of data in stroke patients with a positive extreme value index. Consequently, the estimated conditional extreme quantile indicates that stroke patients with higher blood pressure measurements face an elevated risk of recurrent stroke occurrence at an early stage. This research contributes to the understanding of the relationship between ambulatory blood pressure and recurrent stroke, providing valuable insights for clinical considerations and potential interventions in stroke management.

关键词： censored data Conditional Extreme Quantile Kernel Estimator Weibull Tail Coefficient

ESTIMATION　FOR　THE　AYMPTOTIC　VARIANCE　OF　PARAMETRIC　ESTIMATES　IN　PARTIAL　LINEAR　MODEL　WITH　censored　

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Acta Mathematica Scientia 1996年第2期16卷 192-208页

作者：秦更生蔡雷 Dept. of Math. Sichuan University Chengdu 610064 China

Consider tile partial linear model Y=Xβ+ g(T) + e. Wilers Y is at risk of being censored from the right, g is an unknown smoothing function on [0,1], β is a 1-dimensional parameter to be estimated and e is an unobserved error. In Ref[1,2], it wes proved that the estimator for the asymptotic variance of βn(βn) is consistent. In this paper, we establish the limit distribution and the law of the iterated logarithm for,En, and obtain the convergest rates for En and the strong uniform convergent rates for gn(gn).

关键词： Partial linear model censored data Kernel method Asymptotic normality Thc law of the iterated logarithm.