Hang Yu,Yuanjia Wang,Donglin Zeng
Hang Yu
With growing interest to use black-box machine learning for complex data with many feature variables, it is critical to obtain a prediction model that only depends on a small set of features to maximize generalizability. Therefore, feature ...
William R Palmer,Richard A Davis,Tian Zheng
William R Palmer
We propose a generalized non-linear state-space model for count-valued time series of COVID-19 fatalities. To capture the dynamic changes in daily COVID-19 death counts, we specify a latent state process that involves second-order differenc...
Robust inference for non-linear regression models from the Tsallis score: Application to coronavirus disease 2019 contagion in Italy [0.03%]
基于Tsallis得分的非线性回归模型的稳健推理：应用到意大利新型冠状病毒2019传染情况中的研究
Paolo Girardi,Luca Greco,Valentina Mameli et al.
Paolo Girardi et al.
We discuss an approach of robust fitting on non-linear regression models, in both frequentist and Bayesian approaches, which can be employed to model and predict the contagion dynamics of the coronavirus disease 2019 (COVID-19) in Italy. Th...
Aaron B Wagner,Elaine L Hill,Sean E Ryan et al.
Aaron B Wagner et al.
Social distancing measures have been imposed across the United States in order to stem the spread of COVID-19. We quantify the reduction in the doubling rate, by state, that is associated with this intervention. Using the earlier of K-12 sc...
Yi-Hui Zhou
Yi-Hui Zhou
The problem of detecting the changes in covariance for a single pair of genomic features has been studied in some detail but may be limited in importance or general applicability. For testing equality of covariance matrices of a set of feat...
Doubly Robust Estimation in Observational Studies with Partial Interference [0.03%]
存在部分干扰的观察研究中的双重稳健估计方法
Lan Liu,Michael G Hudgens,Bradley Saul et al.
Lan Liu et al.
Interference occurs when the treatment (or exposure) of one individual affects the outcomes of others. In some settings it may be reasonable to assume individuals can be partitioned into clusters such that there is no interference between i...
Lin Su,Wenbin Lu,Rui Song
Lin Su
In many network-based intervention studies, treatment applied on an individual or his or her own characteristics may also affect the outcome of other connected people. We call this interference along network. Approaches for deriving the opt...
Bias and estimation under misspecification of the risk period in self-controlled case series studies [0.03%]
风险期误指定的自我对照病例系列研究中的偏倚和估计问题
Luis Fernando Campos,Damla Şentürk,Yanjun Chen et al.
Luis Fernando Campos et al.
The self-controlled case series (SCCS) method is useful for estimating the relative incidence (RI) of acute events, such as adverse events (AEs) during a specified risk period following an exposure (e.g., 6-week period after vaccinations or...
Tao Hu,Paul Gallins,Yi-Hui Zhou
Tao Hu
The microbiome is increasingly recognized as an important aspect of the health of host species, involved in many biological pathways and processes and potentially useful as health biomarkers. Taking advantage of high-throughput sequencing t...
Merging K-means with hierarchical clustering for identifying general-shaped groups [0.03%]
结合层次聚类的K均值算法在通用形状组识别中的应用
Anna D Peterson,Arka P Ghosh,Ranjan Maitra
Anna D Peterson
Clustering partitions a dataset such that observations placed together in a group are similar but different from those in other groups. Hierarchical and K-means clustering are two approaches but have different strengths and weaknesses. For ...