Adaptive Clustering and Feature Selection for Categorical Time Series Using Interpretable Frequency-Domain Features [0.03%]
基于可解释频域特征的类别时间序列自适应聚类与特征选择方法研究
Scott A Bruce
Scott A Bruce
This article presents a novel approach to clustering and feature selection for categorical time series via interpretable frequency-domain features. A distance measure is introduced based on the spectral envelope and optimal scalings, which ...
The more data, the better? Demystifying deletion-based methods in linear regression with missing data [0.03%]
数据越多越好？揭秘线性回归中带有缺失数据的删除法
Tianchen Xu,Kun Chen,Gen Li
Tianchen Xu
We compare two deletion-based methods for dealing with the problem of missing observations in linear regression analysis. One is the complete-case analysis (CC, or listwise deletion) that discards all incomplete observations and only uses c...
Dongfeng Wu
Dongfeng Wu
A probability method is developed to decide when to initiate cancer screening for asymptomatic individuals. The probability of incidence is a function of screening sensitivity, time duration in the disease-free state and sojourn time in the...
Estimation of Preclinical State Onset Age and Sojourn Time for Heavy Smokers in Lung Cancer [0.03%]
肺癌高危吸烟人群的癌前病变年龄和滞留时间估计模型
Dongfeng Wu,Shesh N Rai,Albert Seow
Dongfeng Wu
Estimation of the three key parameters: onset age of the preclinical state, sojourn time and screening sensitivity is critical in cancer screening, since all other terms are functions of the three. A novel link function to connect sensitivi...
Pathway Lasso: Pathway Estimation and Selection with High-Dimensional Mediators [0.03%]
高维中介变量下的路径模型估计与选择：路径套索法
Yi Zhao,Xi Luo
Yi Zhao
In many scientific studies, it becomes increasingly important to delineate the pathways through a large number of mediators, such as genetic and brain mediators. Structural equation modeling (SEM) is a popular technique to estimate the path...
Covariate-adjusted hybrid principal components analysis for region-referenced functional EEG data [0.03%]
协变量调整的混合主成分分析在基于脑区的函数型EEG数据分析中的应用研究
Aaron Wolfe Scheffler,Abigail Dickinson,Charlotte DiStefano et al.
Aaron Wolfe Scheffler et al.
Electroencephalography (EEG) studies produce region-referenced functional data via EEG signals recorded across scalp electrodes. The high-dimensional data can be used to contrast neurodevelopmental trajectories between diagnostic groups, fo...
Donghui Yan,Timothy Randolph,Jian Zou et al.
Donghui Yan et al.
Tissue microarray (TMA) images have been used increasingly often in cancer studies and the validation of biomarkers. TACOMA-a cutting-edge automatic scoring algorithm for TMA images-is comparable to pathologists in terms of accuracy and rep...
Bayesian Meta-Regression Model Using Heavy-Tailed Random-effects with Missing Sample Sizes for Self-thinning Meta-data [0.03%]
基于重尾随机效应并含缺失样本大小的自稀疏元数据的贝叶斯元回归模型
Zhihua Ma,Ming-Hui Chen,Yi Tang
Zhihua Ma
Motivated by the self-thinning meta-data, a random-effects meta-analysis model with unknown precision parameters is proposed with a truncated Poisson regression model for missing sample sizes. The random effects are assumed to follow a heav...
Extracting scalar measures from functional data with applications to placebo response [0.03%]
从功能数据中提取标量措施及其在安慰剂反应中的应用
Thaddeus Tarpey,Eva Petkova,Adam Ciarleglio et al.
Thaddeus Tarpey et al.
In controlled and observational studies, outcome measures are often observed longitudinally. Such data are difficult to compare among units directly because there is no natural ordering of curves. This is relevant not only in clinical trial...
A hybrid parametric and empirical likelihood model for evaluating interactions in case-control Studies [0.03%]
病例对照研究中评估相互作用的混合参数和经验模型
Jing Qin,Hong Zhang,Maria Landi et al.
Jing Qin et al.
The case-control design provides an effective way to collect covariate information conditioning on subjects' disease status. The standard logistic regression model can be used to model the interaction between two covariates under such a des...