18 citations · 52 across the 12 of their papers we have counts for
12 papers
Moment-Based Selection of Multiresponse Linear Mixed-Effects Models
Yifan Chen, Yuedong Wang, Guo Yu
We propose MOMENT (\textbf{MO}ment-Based \textbf{M}ixed-\textbf{E}ffects Selectio\textbf{N} and Es\textbf{T}imation), a stage-wise moment-based framework that exploits second-order…
Discriminative classification with generative features: bridging Naive Bayes and logistic regression
Zachary Terner, Alexander Petersen, Yuedong Wang
We introduce Smart Bayes, a new classification framework that bridges generative and discriminative modeling by integrating likelihood-ratio-based generative features into a logist…
A Multiprocess State Space Model with Feedback and Switching for Patterns of Clinical Measurements Associated with COVID-19
Xiaoran Ma, Wensheng Guo, Peter Kotanko +1
Clinical measurements, such as body temperature, are often collected over time to monitor an individual's underlying health condition. These measurements exhibit complex temporal d…
Sequential Kalman filter for fast online changepoint detection in longitudinal health records
Hanmo Li, Yuedong Wang, Mengyang Gu
This article introduces the sequential Kalman filter, a computationally scalable approach for online changepoint detection with temporally correlated data. The temporal correlation…
A Nonparametric Mixed-Effects Mixture Model for Patterns of Clinical Measurements Associated with COVID-19
Xiaoran Ma, Wensheng Guo, Mengyang Gu +3
Some patients with COVID-19 show changes in signs and symptoms such as temperature and oxygen saturation days before being positively tested for SARS-CoV-2, while others remain asy…
Sparse Positive-Definite Estimation for Covariance Matrices with Repeated Measurements
Sunpeng Duan, Guo Yu, Juntao Duan +1
Repeated measurements are common in many fields, where random variables are observed repeatedly across different subjects. Such data have an underlying hierarchical structure, and…
Fixed-effects model: the most convincing model for meta-analysis with few studies
Enxuan Lin, Tiejun Tong, Yong Chen +1
According to Davey et al. (2011) with a total of 22,453 meta-analyses from the January 2008 Issue of the Cochrane Database of Systematic Reviews, the median number of studies inclu…
Low Rank Approximation for Smoothing Spline via Eigensystem Truncation
Danqing Xu, Yuedong Wang
Smoothing splines provide a powerful and flexible means for nonparametric estimation and inference. With a cubic time complexity, fitting smoothing spline models to large data is c…
Combining Smoothing Spline with Conditional Gaussian Graphical Model for Density and Graph Estimation
Runfei Luo, Anna Liu, Yuedong Wang
Multivariate density estimation and graphical models play important roles in statistical learning. The estimated density can be used to construct a graphical model that reveals con…
Smoothing Spline Semiparametric Density Models
Jian Shi, Jiahui Yu, Anna Liu +1
Density estimation plays a fundamental role in many areas of statistics and machine learning. Parametric, nonparametric and semiparametric density estimation methods have been prop…
Optimal variance estimation without estimating the mean function
Tiejun Tong, Yanyuan Ma, Yuedong Wang
We study the least squares estimator in the residual variance estimation context. We show that the mean squared differences of paired observations are asymptotically normally distr…
Nonparametric spectral analysis with applications to seizure characterization using EEG time series
Li Qin, Yuedong Wang
Understanding the seizure initiation process and its propagation pattern(s) is a critical task in epilepsy research. Characteristics of the pre-seizure electroencephalograms (EEGs)…