Marinela Capanu,Mihai Giurcanu,Colin B Begg et al.
Marinela Capanu et al.
A novel variable selection method for low-dimensional generalized linear models is introduced. The new approach called AIC OPTimization via STABility Selection (OPT-STABS) repeatedly subsamples the data, minimizes Akaike's Information Crite...
Wei Xiong,Yaxian Chen,Shuangge Ma
Wei Xiong
For many practical high-dimensional problems, interactions have been increasingly found to play important roles beyond main effects. A representative example is gene-gene interaction. Joint analysis, which analyzes all interactions and main...
Shi Zhao,Giorgos Bakoyannis,Spencer Lourens et al.
Shi Zhao et al.
Estimation of nonlinear curves and surfaces has long been the focus of semiparametric and nonparametric regression analysis. What has been less studied is the comparison of nonlinear functions. In lower-dimensional situations, inference typ...
Abdul-Nasah Soale
Abdul-Nasah Soale
Many existing sufficient dimension reduction methods are designed for regression with predictors that are elliptically distributed, which limits their application in real data analyses. Projection expectile regression (PER) is proposed as a...
Specification testing for ordinary differential equation models with fixed design and applications to COVID-19 epidemic models [0.03%]
常微分方程模型的规范检验及其在COVID-19流行病模型中的应用
Ran Liu,Lixing Zhu
Ran Liu
Checking the models about the ongoing Coronavirus Disease 2019 (COVID-19) pandemic is an important issue. Some famous ordinary differential equation (ODE) models, such as the SIR and SEIR models have been used to describe and predict the ep...
Elise F Palzer,Christine H Wendt,Russell P Bowler et al.
Elise F Palzer et al.
Analyzing multi-source data, which are multiple views of data on the same subjects, has become increasingly common in molecular biomedical research. Recent methods have sought to uncover underlying structure and relationships within and/or ...
Group linear non-Gaussian component analysis with applications to neuroimaging [0.03%]
群体线性非高斯成分分析及其在神经影像学中的应用
Yuxuan Zhao,David S Matteson,Stewart H Mostofsky et al.
Yuxuan Zhao et al.
Independent component analysis (ICA) is an unsupervised learning method popular in functional magnetic resonance imaging (fMRI). Group ICA has been used to search for biomarkers in neurological disorders including autism spectrum disorder a...
Yan Zhong,Huiyan Sang,Scott J Cook et al.
Yan Zhong et al.
Large spatial datasets with many spatial covariates have become ubiquitous in many fields in recent years. A question of interest is to identify which covariates are likely to influence a spatial response, and whether and how the effects of...
Brain Waves Analysis Via a Non-Parametric Bayesian Mixture of Autoregressive Kernels [0.03%]
基于非参数贝叶斯自回归核的脑电波分析
Guilllermo Granados-Garcia,Marc Fiecas,Shahbaba Babak et al.
Guilllermo Granados-Garcia et al.
The standard approach to analyzing brain electrical activity is to examine the spectral density function (SDF) and identify frequency bands, defined a priori, that have the most substantial relative contributions to the overall variance of ...
Generalisations of a Bayesian decision-theoretic randomisation procedure and the impact of delayed responses [0.03%]
贝叶斯决策论随机化程序的推广及延迟响应的影响
S Faye Williamson,Peter Jacko,Thomas Jaki
S Faye Williamson
The design of sequential experiments and, in particular, randomised controlled trials involves a trade-off between operational characteristics such as statistical power, estimation bias and patient benefit. The family of randomisation proce...