Xiangyu Liu,Jing Ning,Xuming He et al.
Xiangyu Liu et al.
When no single outcome is sufficient to capture the multidimensional impairments of a disease, investigators often rely on multiple outcomes for comprehensive assessment of global disease status. Methods for assessing covariate effects on g...
Simultaneous confidence bands for functional data using the Gaussian Kinematic formula [0.03%]
基于高斯动力学公式的函数数据的同时置信带
Fabian J E Telschow,Armin Schwartzman
Fabian J E Telschow
We propose a construction of simultaneous confidence bands (SCBs) for functional parameters over arbitrary dimensional compact domains using the Gaussian Kinematic formula of t-processes (tGKF). Although the tGKF relies on Gaussianity, we s...
Efficient empirical likelihood inference for recovery rate of COVID19 under double-censoring [0.03%]
双区间删失下COVID-19恢复率的高效经验似然推断
Jie Hu,Wei Liang,Hongsheng Dai et al.
Jie Hu et al.
Doubly censored data are very common in epidemiology studies. Ignoring censorship in the analysis may lead to biased parameter estimation. In this paper, we highlight that the publicly available COVID19 data may involve high percentage of d...
Bi- s*-Concave Distributions [0.03%]
双s-凹分布
Nilanjana Laha,Zhen Miao,Jon A Wellner
Nilanjana Laha
We introduce new shape-constrained classes of distribution functions on R , the bi-s*-concave classes. In parallel to results of Dümbgen et al. (2017) for what they called the class of bi-log-concave distribution functions, we show that ev...
Optimal Sparse Eigenspace and Low-Rank Density Matrix Estimation for Quantum Systems [0.03%]
量子系统的最优稀疏特征空间和低秩密度矩阵估计
Tony Cai,Donggyu Kim,Xinyu Song et al.
Tony Cai et al.
Quantum state tomography, which aims to estimate quantum states that are described by density matrices, plays an important role in quantum science and quantum technology. This paper examines the eigenspace estimation and the reconstruction ...
An Orthogonally Equivariant Estimator of the Covariance Matrix in High Dimensions and for Small Sample Sizes [0.03%]
高维小样本情形下协方差阵的正交不变估计量
Samprit Banerjee,Stefano Monni
Samprit Banerjee
We introduce an estimation method of covariance matrices in a high-dimensional setting, i.e., when the dimension of the matrix, p, is larger than the sample size n. Specifically, we propose an orthogonally equivariant estimator. The eigenve...
Efficient analysis of time-to-event endpoints when the event involves a continuous variable crossing a threshold [0.03%]
当事件涉及连续变量跨越阈值时，时间-终点结局的有效分析方法
Chien-Ju Lin,James M S Wason
Chien-Ju Lin
In many trials, the duration between patient enrolment and an event occurring is used as the efficacy endpoint. Common endpoints of this type include the time until relapse, progression to the next stage of a disease, or time until remissio...
Hyung Park,Eva Petkova,Thaddeus Tarpey et al.
Hyung Park et al.
In a regression model for treatment outcome in a randomized clinical trial, a treatment effect modifier is a covariate that has an interaction with the treatment variable, implying that the treatment efficacies vary across values of such a ...
Pao-Sheng Shen
Pao-Sheng Shen
In this note, we consider data subjected to middle censoring where the variable of interest becomes unobservable when it falls within an interval of censorship. We demonstrate that the nonparametric maximum likelihood estimator (NPMLE) of d...
Dongliang Wang,Tong Tong Wu,Yichuan Zhao
Dongliang Wang
The current penalized regression methods for selecting predictor variables and estimating the associated regression coefficients in the sparse Cox model are mainly based on partial likelihood. In this paper, a bias-corrected empirical likel...