Journal of Data Science, v.19, no.2

Welcome to the Philosophy of Data Science Section

By Glen Wright Colopy

• Full Text (PDF): [72.63kB]

Journal of Data Science, v.19, no.2

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

By Ting Tian, Jianbin Tan, Yukang Jiang, Xueqin Wang, and Heping Zhang

• Full Text (PDF): [1.33MB]

Journal of Data Science, v.19, no.2

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”

By Jeffrey S. Morris, and Jing Huang

• Full Text (PDF): [72.34kB]

Journal of Data Science, v.19, no.2

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”

By Corbin Quick and Xihong Lin

• Full Text (PDF): [59.09kB]

Journal of Data Science, v.19, no.2

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”

By Yishu Xue, Hou-Cheng Yang, Yuqing Pan, and Guanyu Hu

• Full Text (PDF): [71.14kB]

Journal of Data Science, v.19, no.2

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”

By Shan Yu, Guannan Wang, and Li Wang

• Full Text (PDF): [276.83kB]

Journal of Data Science, v.19, no.2

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”

By Chuanrong Zhang, and Xinba Li

• Full Text (PDF): [580.12kB]

Journal of Data Science, v.19, no.2

Rejoinder: “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”

By Ting Tian, Jianbin Tan, Yukang Jiang, Xueqin Wang, and Heping Zhang

• Full Text (PDF): [582.85kB]

Journal of Data Science, v.19, no.2

Methods, Challenges, and Practical Issues of COVID-19 Projection: A Data Science Perspective

By Myungjin Kim, Zhiling Gu, Shan Yu, Guannan Wang, and Li Wang

• Full Text (PDF): [1.23MB]

Journal of Data Science, v.19, no.2

Testing for COVID-19: Some Statistical Issues

By Grace Y. Yi, Wenqing He, Dennis K. J. Lin, and Chun Ming Yu

• Full Text (PDF): [249.40kB]

Journal of Data Science, v.19, no.2

Assessment of Effects of Age and Gender on the Incubation Period of COVID-19 with a Mixture Regression Model

By Siming Zheng, Jing Qin, and Yong Zhou

• Full Text (PDF): [207.89kB]

Journal of Data Science, v.19, no.2

Time Series Regression Models for COVID-19 Deaths

By Marinho G. Andrade, Jorge A. Achcar, Katiane S. Conceição, and Nalini Ravishanker

• Full Text (PDF): [515.42kB]

Journal of Data Science, v.19, no.2

AICov: An Integrative Deep Learning Framework for COVID-19 Forecasting with Population Covariates

By Geoffrey C. Fox, Gregor von Laszewski, Fugang Wang1, and Saumyadipta Pyne

• Full Text (PDF): [647.39kB]

Journal of Data Science, v.19, no.2

Five Critical Genes Related to Seven COVID-19 Subtypes: A Data Science Discovery Statistical Challenges in the Analysis of Sequence and Structure Data for the COVID-19 Spike Protein

By Shiyu He and Samuel W.K. Wong

• Full Text (PDF): [3.07MB]

Journal of Data Science, v.19, no.2

Community Detection in Google Searches Related to“Coronavirus”

By Philip D. Waggoner

• Full Text (PDF): [955.88kB]

Journal of Data Science, v.19, no.2

Estimating the Number of Infected Cases in COVID-19 Pandemic

By Donghui Yan, Ying Xu, and Pei Wang

• Full Text (PDF): [620.68kB]