Summary
Research Interests
Latent variable modeling, Bayesian spatial and spatio-temporal analysis, Bayesian parametric and nonparametric regression models, statistical computing, advanced Markov chain Monte Carlo methods, infectious disease modeling/forecasting, Group testing data analysis, pooled biomarker modeling, and biostatistical and epidemiological applications.
Publications
- Liu, Y., Watson, S., Lund, R., Nordone, S., McMahan, C., and Yabsley, M. (2017). A Bayesian spatio-temporal model for forecasting Anaplasma species seroprevalence in domestic dogs within the contiguous United States., 12(7): e0182028..
- Watson, S., Liu, Y., Gettings, J., Lund, R., Nordone, S., McMahan, C., and Yabsley, M. (2017). A Bayesian Spatio-Temporal Model for Forecasting the Prevalence of Antibodies to Borrelia burgdorferi, Causative Agent of Lyme Disease, in Domestic Dogs within the Contiguous United States. PLOS ONE, 12(5): e0174428.
- Liu, Y., McMahan, C., and Gallagher, C. (2017+). A general regression framework for the regression analysis of pooled biomarker assessments. Statistics in Medicine, 36(15), 2363-2377.
- Liu, Y., Lund, R., Nordone, S., Yabsley, M., and McMahan, C. (2017). A Bayesian spatio-temporal model for forecasting the prevalence of antibodies to Ehrlichia in domestic dogs within the contiguous United States. Parasites Vectors, 10:138.
- Bowman, D., Liu, Y., McMahan, C., Nordone, S., Yabsley, M., and Lund, R. (2016). Forecasting United States heartworm diroflaria immitis prevalence in dogs. Parasites Vectors, 9:540.
- Yao, C., Liu, Y., and Zhan, M. (2011). Frequency-resonance-enhanced vibrational resonance in bistable systems, it Physical Review E, bf 83, 061122.
- Zhao, Q., Yi, M. and Liu, Y. (2011). Spatial distribution and dose-response relationship for different operation modes in a reaction-diffusion model of the MAPK cascade, Physical Biology, bf 8, 055004.
Education
- PhD from Clemson University, Clemson, SC