Parametric Inference on Longitudinal Data Driven by Long Distance Memory

来源 :上海交通大学 | 被引量 : 0次 | 上传用户：ait123123

【摘要】

：

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

【作者】

：

Rachid Senoussi Mesbah Mounir

【机构】

：

Biostatistique et Processus Spatiaux(BioSP),INRA,Site Agroparc,84914 Avignon,France

【出处】

：

上海交通大学

【发表日期】

：

2016年4期

【关键词】

：

Long range dependance Longitudinal Latent Rasch model Quality of Life

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

其他文献

How to work beyond being a statistical copycat in China Medicines Development?

In China medicines development,factors,including medical practice,CMC,regulatory,and many others,often prevent researchers from joining Multi-Regional Clinical Trials.

会议

Lasso adjustments of treatment effect estimates in randomized experiments

We provide a principled way for investigators to analyze randomized experiments when the number of covariates is large.Investigators often use linear multivariate regression to analyze randomized expe

会议

randomized experimentNeyman-Rubin modelaverage treatment effecthigh-dimension

CLT for linear spectral statistics of large dimensional sample covariance matrices with dependent da

This paper investigates the central limit theorem for linear spectral statistics of high dimensional sample covariance matrices of the form Bn = n-1∑nj =1 Qxjx*j Q* where Q is a nonrandom matrix of di

会议

Large sample covariance matriceslinear spectral statisticscentral limit theore

Spatial Covariance Function with Stochastic Volatility

Geostatistical data has received great attention in recent years.To model spatial dependence of such type of data,the spatial covariance function is commonly employed.

会议

Spatial Covariance FunctionSpatial Missing DataStochastic VolatilitySpatial K

GRAPHICAL LATENT REGRESSION-MULTINOMIAL MIXTURE FOR MODELING COMPLEX DEPENDENCE

We have seen complex dependence in many real fields including biology,advertising,and real estate.Their data are complex and heterogeneous in general.

会议

Multinomial MixtureMarkov Random Field

ON THE INCREASING PATHS IN ACCESSIBILITY PERCOLATION

Consider a regular n-ary tree of height h,where n = αh.Each vertex is assigned a real number,called its fitness.Except that the fitness value of the root is always assumed to be 0,the fitness values a

会议

Increasing pathsaccessibility percolationregular tree

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

其他学术论文