Yuqing Pan
Florida State University
15 Papers
16 Citations
Yuqing Pan is an academic researcher from Florida State University. The author has contributed to research in topics: Linear discriminant analysis & Tensor. The author has an hindex of 4, co-authored 11 publications. Previous affiliations of Yuqing Pan include Microsoft & Zhejiang University.
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Papers
Covariate-Adjusted Tensor Classification in High Dimensions
Yuqing Pan,Qing Mai,Xin Zhang +2 more
TL;DR: The authors predict a categorical response based on a high-dimensional tensor (i.e., multi-dimensional array) and additional covariates, which is often of great interest in contemporary scientific research.
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TULIP: A Toolbox for Linear Discriminant Analysis with Penalties
Yuqing Pan,Qing Mai,Xin Zhang +2 more
TL;DR: The R package TULIP integrates several popular high-dimensional LDA-based methods and provides a comprehensive and user-friendly toolbox for linear, semi-parametric and tensor-variate classification.
11
Time fused coefficient SIR model with application to COVID-19 epidemic in the United States
TL;DR: The proposed model discovers the underlying time homogeneity pattern for the SIR model's transmission rate and removal rate via Bayesian shrinkage priors through time fused coefficients.
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•Posted Content
TULIP: A Toolbox for Linear Discriminant Analysis with Penalties
Yuqing Pan,Qing Mai,Xin Zhang +2 more
TL;DR: TULIP as mentioned in this paper integrates several popular high-dimensional LDA-based methods and provides a comprehensive and user-friendly toolbox for linear, semi-parametric and tensor-variate classification.
3
Discussion of “Evaluate the Risk of Resumption of Business for the States of New York, New Jersey and Connecticut via a Pre-Symptomatic and Asymptomatic Transmission Model of COVID-19”
Abstract: Tian et al. (2021) proposed the Susceptible-Unidentified infectious-Self-healing without being confirmed-Confirmed cases (SIHC) model that divides the population into four compartments as opposed to three, which is assumed by the popular Susceptible-Infectious-Recovered model (SIR; Kermack and McKendrick, 1927). Specifically, the authors divided the infectious compartment into those who exhibit symptoms, and asymptomatic carriers. Instead of using a recovered/removed compartment, the authors assumed that individuals in the infectious compartment eventually end up confirmed and hospitalized or quarantined, or self-healed without being confirmed. This novel segregation is of practical value as it matches the current practices in fighting COVID-19. In the rest of this discussion, we comment on the approach that the authors have proposed, and suggest some possible extension of the work for future research.