Extreme quantile estimation for partial functional linear regression models with heavy-tailed distributions [0.03%]
具有重尾分布的部分功能线性回归模型的极端分位数估计
Hanbing Zhu,Yehua Li,Baisen Liu et al.
Hanbing Zhu et al.
In this article, we propose a novel estimator of extreme conditional quantiles in partial functional linear regression models with heavy-tailed distributions. The conventional quantile regression estimators are often unstable at the extreme...
Integrating Information from Existing Risk Prediction Models with No Model Details [0.03%]
整合现有的风险预测模型中的信息（无需模型详细信息）
Peisong Han,Jeremy M G Taylor,Bhramar Mukherjee
Peisong Han
Consider the setting where (i) individual-level data are collected to build a regression model for the association between an event of interest and certain covariates, and (ii) some risk calculators predicting the risk of the event using le...
Efficient multiple change point detection for high-dimensional generalized linear models [0.03%]
高效高维广义线性模型的多重变点检测方法
Xianru Wang,Bin Liu,Xinsheng Zhang et al.
Xianru Wang et al.
Change point detection for high-dimensional data is an important yet challenging problem for many applications. In this paper, we consider multiple change point detection in the context of high-dimensional generalized linear models, allowin...
Estimation of conditional cumulative incidence functions under generalized semiparametric regression models with missing covariates, with application to analysis of biomarker correlates in vaccine trials [0.03%]
带有缺失协变量的广义半参数回归模型下的条件累积发病函数估计及其在疫苗试验生物标志物相关性分析中的应用
Yanqing Sun,Fei Heng,Unkyung Lee et al.
Yanqing Sun et al.
This article studies generalized semiparametric regression models for conditional cumulative incidence functions with competing risks data when covariates are missing by sampling design or happenstance. A doubly-robust augmented inverse pro...
Estimation of SARS-CoV-2 antibody prevalence through serological uncertainty and daily incidence [0.03%]
通过血清学不确定性和每日发病率估算SARS-CoV-2抗体阳性率
Liangliang Wang,Joosung Min,Renny Doig et al.
Liangliang Wang et al.
Serology tests for SARS-CoV-2 provide a paradigm for estimating the number of individuals who have had an infection in the past (including cases that are not detected by routine testing, which has varied over the course of the pandemic and ...
Leying Guan,Robert Tibshirani
Leying Guan
We propose a simple method for evaluating the model that has been chosen by an adaptive regression procedure, our main focus being the lasso. This procedure deletes each chosen predictor and refits the lasso to get a set of models that are ...
A grouped beta process model for multivariate resting-state EEG microstate analysis on twins [0.03%]
多变量静息态EEG微状态孪生分析的分组贝塔过程模型
Brian Hart,Stephen Malone,Mark Fiecas
Brian Hart
EEG microstate analysis investigates the collection of distinct temporal blocks that characterize the electrical activity of the brain. Brain activity within each microstate is stable, but activity switches rapidly between different microst...
Extended Bayesian endemic-epidemic models to incorporate mobility data into COVID-19 forecasting [0.03%]
扩展bayesian地方性大流行模型以将移动数据纳入COVID-19预测中
Dirk Douwes-Schultz,Shuo Sun,Alexandra M Schmidt et al.
Dirk Douwes-Schultz et al.
Forecasting the number of daily COVID-19 cases is critical in the short-term planning of hospital and other public resources. One potentially important piece of information for forecasting COVID-19 cases is mobile device location data that ...
Characterizing the COVID-19 dynamics with a new epidemic model: Susceptible-exposed-asymptomatic-symptomatic-active-removed [0.03%]
一种新的流行病模型下的COVID-19动力学特征：潜伏者-无症状感染者-有症状感染者-活跃患者-移除者模型
Grace Y Yi,Pingbo Hu,Wenqing He
Grace Y Yi
The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread stealthily and presented a tremendous threat to the public. It is important to investigate the transmission dyna...
Estimating design operating characteristics in Bayesian adaptive clinical trials [0.03%]
贝叶斯适应性临床试验中的设计操作特性估计
Shirin Golchi
Shirin Golchi
Bayesian adaptive designs have gained popularity in all phases of clinical trials with numerous new developments in the past few decades. During the COVID-19 pandemic, the need to establish evidence for the effectiveness of vaccines, therap...