The Fine-Gray Model Under Interval Censored Competing Risks Data [0.03%]
区间截断下Fine-Gray模型的竞争风险分析方法研究
Chenxi Li
Chenxi Li
We consider semiparametric analysis of competing risks data subject to mixed case interval censoring. The Fine-Gray model (Fine & Gray, 1999) is used to model the cumulative incidence function and is coupled with sieve semiparametric maximu...
T Tony Cai,Anru Zhang
T Tony Cai
Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantee...
Influence assessment in censored mixed-effects models using the multivariate Student's- t distribution [0.03%]
基于多元Student's-t分布的广义线性混合效应模型的影响分析
Larissa A Matos,Dipankar Bandyopadhyay,Luis M Castro et al.
Larissa A Matos et al.
In biomedical studies on HIV RNA dynamics, viral loads generate repeated measures that are often subjected to upper and lower detection limits, and hence these responses are either left- or right-censored. Linear and non-linear mixed-effect...
Integrative correlation: Properties and relation to canonical correlations [0.03%]
综合相关性：性质及其与典型相关性的关系
Leslie Cope,Daniel Q Naiman,Giovanni Parmigiani
Leslie Cope
The integrative correlation coefficient was developed to facilitate the validation of expression microarray results in public datasets, by identifying genes that are reproducibly measured across studies and even across microarray platforms....
Weidong Liu,Xi Luo
Weidong Liu
This paper proposes a new method for estimating sparse precision matrices in the high dimensional setting. It has been popular to study fast computation and adaptive procedures for this problem. We propose a novel approach, called Sparse Co...
Equivariant minimax dominators of the MLE in the array normal model [0.03%]
数组常规模型中MLE的equivariant minimax占优解
David Gerard,Peter Hoff
David Gerard
Inference about dependencies in a multiway data array can be made using the array normal model, which corresponds to the class of multivariate normal distributions with separable covariance matrices. Maximum likelihood and Bayesian methods ...
Jack Cuzick,Zihua Yang
Jack Cuzick
Most models for categorical data rely on linear models in which higher order interactions are limited, usually to second order terms. Here we explore a dataset where second order interactions lead unavoidably to high order interactions. How...
Nonparametric Functional Central Limit Theorem for Time Series Regression with Application to Self-normalized Confidence Interval [0.03%]
非参数函数型中心极限定理在时间序列回归中的应用及自规范化置信区间法
Seonjin Kim,Zhibiao Zhao,Xiaofeng Shao
Seonjin Kim
This paper is concerned with the inference of nonparametric mean function in a time series context. The commonly used kernel smoothing estimate is asymptotically normal and the traditional inference procedure then consistently estimates the...
Effective Degrees of Freedom and Its Application to Conditional AIC for Linear Mixed-Effects Models with Correlated Error Structures [0.03%]
相关误差结构下的线性混合效应模型的有效自由度及其在条件AIC中的应用
Rosanna Overholser,Ronghui Xu
Rosanna Overholser
The effective degrees of freedom is a useful concept for describing model complexity. Recently the number of effective degrees of freedom has been shown to relate to the concept of conditional Akaike information (cAI) in the mixed effects m...
Seonjin Kim,Zhibiao Zhao
Seonjin Kim
Most existing works on specification testing assume that we have direct observations from the model of interest. We study specification testing for Markov models based on contaminated observations. The evolving model dynamics of the unobser...