A Note on High Dimensional Z-Estimators

来源 :上海交通大学 | 被引量 : 0次 | 上传用户：gang098

【摘要】

：

【作者】

：

Fang Han Sheng Xu

【机构】

：

Department of Statistics,University of Washington,98195,USA

【出处】

：

上海交通大学

【发表日期】

：

2016年4期

【关键词】

：

linear approximation Z-estimator exponential inequality high dimension spatial m

下载到本地 , 更方便阅读

下载此文赞助VIP

声明 : 本文档内容版权归属内容提供方 , 如果您对本文有版权争议 , 可与客服联系进行内容授权或下架

论文部分内容阅读

　　In this note we provide a simple framework to study Z-estimators in high dimensions.Of interest is the setting where the number of parameters p < n increases with the sample size n.As the main result,strong high dimensional linearization of Z-estimators proves to hold only under a classic Huber-type smoothness condition on the estimating equations.Our results apply to spatial median,giving sharp exponential-type inequalities.They extend the results in He and Shao(2000)and Zou et al.(2013).

其他文献

HYBRID GRAPHICAL LEAST SQUARE ESTIMATION AND ITS APPLICATION IN PORTFOLIO SELECTION

A novel regression method based on the idea of graphical models is proposed to deal with the portfolio optimisation problem within the Markowitz mean-variance framework,when the number of assets V is

会议

Graphical ModelGraphical Least SquaresLASSORidge RegressionUnbiased Estimati

Maximum likelihood inference for a large precision matrix

Inference concerning Gaussian graphical models involves pairwise conditional dependencies on Gaus-sian random variables.In such a situation,regularization of a certain form is often employed to treat

会议

Constrained likelihood inferenceGeneralized Wilks phenomenonGraphical modelsH

Statistical estimation for heteroscedastic transformation regression models with unknown transformat

Consider a censored heteroscedastic transformation regression model where both the transformation function and the error distribution function are completely unknown.

会议

Transformation regression modelheteroscedasticitycensored data

Multiple Imputation for Handling Missing Data under Informative Sampling

Multiple imputation is popular for handling item nonresponse in survey sampling.The current multiple imputation techniques with complex survey data are developed with the assumption that the sampling

会议

Approximate Bayesian ComputationBayesian inferenceComplex samplingItem nonres

Parametric Inference on Longitudinal Data Driven by Long Distance Memory

Computerized monitoring of patients health status is an important issue in modern medicine.Patient-reported outcome(PRO)is most of the time assessed through a self-questionnaire,where item responses a

会议

Long range dependanceLongitudinalLatentRasch modelQuality of Life

Item Response Theory(IRT)models represent a well-known instrument to measure latent variables on the basis of the observed responses to a set of items.In their original formulation IRT models assume t

会议

Finite-mixture modelItem Response TheoryLatent class modelMultidimensionality

Statistical Inference of Latent Class Models with Application to Mental Health Disorders

This talk gives an overview of the Q-matrix based diagnostic classification models and the associated statistical inference arising from analysis of item response data.Attention will be given to model

会议

Latent class modelvariable selectionQ-matrixitem response data

DESIGN AND ANALYSIS OF MULTI-REGIONAL CLINICAL TRIALS:REGULATORY AND STATISTICAL PERSPECTIVE

Multi-Regional Clinical Trials(MRCTs)have been already common practice for the global simultaneous development of new drugs,and to design and analyze a MRCT is the key for successful simultaneous appr

会议

Multi-Regional Clinical Trialsregional effectsconsistency

ALTERNATIVE TECHNIQUES OF CONSTRUCTING EMPIRICAL BAYES(EB)CONFIDENCE INTERVALS FOR HIERARCHICAL NEGA

The negative binomial(NB)distribution is commonly used to model count data in many areas of research.We use a parametric hierarchical empirical Bayes(EB)approach for estimating the parameters of(NB)ge

会议

Negative BinomialHierarchical Empirical BayesEstimationGeneralized Linear Mod

Isotropic random fields and point processes on graphs and their edges

We present theoretical work on the existence of second order isotropic stochastic processes and non-homogeneous spatial point processes defined on the edges and the vertices of a graph.The edges of su

会议

GraphsIsotropic Random FieldsSpatial Point Processes

A Note on High Dimensional Z-Estimators

与本文相关的学术论文