Publications
Research Papers
T. Wang and S.I. Resnick. Measuring Reciprocity in a Directed Preferential Attachment Network. Advances in Applied Probability, DOI: 10.1017/apr.2021.52, 2022.
T. Wang and S.I. Resnick. Asymptotic Dependence of In- and Out-Degrees in a Preferential Attachment Model with Reciprocity. Extremes, DOI: 10.1007/s10687-022-00439-5, 2022.
T. Wang and P. Zhang. Hybrid Random Networks Mixing Preferential Attachment with Uniform Attachment Mechanisms. Annals of the Institute of Statistical Mathematics, to appear, DOI: 10.1007/s10463-022-00827-5, 2022.
C. Tang, T. Wang and P. Zhang. Functional data analysis: An application to COVID-19 data in the United States. Quantitative Biology, to appear, 2022+.
B. Das, T. Wang and G. Dai. Asymptotic Behavior of Common Connections in Sparse Random Networks. Methodology and Computing in Applied Probability, DOI: 10.1007/s11009-021-09900-7, 2021.
P. Zhang, T. Wang and J. Yan. PageRank centrality and algorithms for weighted, directed networks. Physica A: Statistical Mechanics and its Applications, DOI:10.1016/j.physa.2021.126438, 2021.
T. Wang and S.I. Resnick. Common growth patterns in regional communication networks: a point process approach. Journal of Data Science, DOI: 10.6339/21-JDS1021, 2021.
T. Wang and J. Yan. Discussion of On Studying Extreme Values and Systematic Risks with Nonlinear Time Series Models and Tail Dependence Measures”. Statistical Theory and Related Fields, 2021. DOI: 10.1080/24754269.2020.1869897.
P. Zhang, T. Wang and S.X. Xie. Meta-analysis of several epidemic characteristics of COVID-19. Journal of Data Science, 18: 536-549, 2020.
T. Wang and S.I. Resnick. Degree growth rates and index estimation in a directed preferential attachment model. Stochastic Processes and their Applications, 130(2): 878-906, 2020.
H. Drees, A. Jan en, S.I. Resnick and T. Wang. On a minimum distance procedure for threshold selection in tail analysis. SIAM Journal on Mathematics of Data Science, 2(1): 75-102, 2020.
P. Wan, T. Wang, R.A. Davis, and S.I. Resnick. Are extreme value estimation methods useful for network data? Extremes, 23(1): 171-195, 2020.
T. Wang and S.I. Resnick. Consistency of Hill Estimators in a Linear Preferential Attachment Model. Extremes, 22(1): 1-28, 2019.
T. Wang and S.I. Resnick. Multivariate Regular Variation of Discrete Mass Functions with Applications to Preferential Attachment Networks. Methodology and Computing in Applied Probability, 20:1029-1042, 2018.
P. Wan, T. Wang, R.A. Davis and S.I. Resnick. Fitting the Linear Preferential Attachment Model. Electronic Journal of Statistics, 11(2):3738-3780, 2017.
T. Wang and S.I. Resnick. Asymptotic Normality of In- and Out-Degree Counts in a Preferential Attachment Model. Stochastic Models, 33(2):229-255, 2017.
Y. Fan, P. Griffin, R.A. Maller, A. Szimayer and T. Wang. The Effects of Largest Claims and Excess of Loss Reinsurance on a Company’s Ruin Time and Valuation, Risks, 5(1):3, 2017.
Preprints
T. Wang and S.I. Resnick. Random Networks with Heterogeneous Reciprocity Levels. arXiv:2208.00348. Submitted to Annals of Applied Probability, 2022.
D. Cirkovic, T. Wang and X. Zhang. Likelihood-based Changepoint Detection in Preferential Attachment Networks. arXiv:2206.01076. Submitted to Biometrika, 2022.
J. Wang, Y. Hou, X. Li and T. Wang. EVIboost for the Prediction of Extreme Value Index under Heterogeneous Extremes. arXiv:2205.14512. Submitted to Journal of Data Science, 2022.
D. Cirkovic, T. Wang and S.I. Resnick. Preferential Attachment with Reciprocity: Properties and Estimation. arXiv:2201.03769. Submitted to Stochastic System, 2022.
T. Wang, J. Yan, Y. Yuan and P. Zhang. Generating Directed Networks with Predetermined Assortativity Measures. arXiv:2201.03451. Submitted to Statistics and Computing, 2022.
T. Wang and S.I. Resnick. A directed preferential attachment model with Poisson Measurement. arXiv preprint: 2008.07005. Submitted to Methodology and Computing of Applied Probability, 2022.