# HaiYing Wang

Department of Statistics

University of Connecticut

Room 319 Philip E. Austin Building

215 Glenbrook Rd. U-4120

Storrs, CT 06269-4120

Phone: (860) 486-6142

haiying.wang@uconn.edu

### About Me

- I am an Assistant Professor in the Department of Statistics, at the University of Connecticut.
- I was an Assistant Professor in the Department of Mathematics & Statistics, at the University of New Hampshire.
- I obtained my PhD from the Department of Statistics, at the University of Missouri, under the supervision of Professor Nancy Flournoy.
- I obtained my MS from the Division of Statistical Science, Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, under the supervision of Professor Guohua Zou.
- I worked as an engineer in the R & D center of Midea Group.
- I obtained my BE from School of Aeronautical Science and Engineering, Beijing University of Aeronautics and Astronautics.
- Here is my CV.

### Research Interests

- Incomplete data analysis
- Model selection and model averaging
- Nonparametric and semi-parametric regression
- Optimum experimental design
- Sub-sample methods for big data

### Publications

- Feng, S., Ding, W.,
**Wang, H.**, Yu, Z., Chen, Y., Zhang, Y. and Xiao, H. (2008). Sampling procedures for inspection by attributes-Part 3: Skip-lot sampling procedures. In Chinese National Standard, GB/T2828.3-2008. **Wang, H.**, Zhang, X. and Zou, G. (2009). Frequentist model averaging estimation: a review.*Journal of Systems Science and Complexity*,**22**(4), 732-748. pdf- Kozak, M.,
**Wang, H.**(2010). On stochastic optimization in sample allocation among strata.*METRON*, LXVIII n.1, pp. 95-103. pdf **Wang, H.**and Zou, G. (2012). Frequentist Model Averaging Estimation for Linear Errors-in-Variables Models.*Journal of Systems Science and Mathematical Science*,**32**(2), 1-14. pdf**Wang, H.**, Zou, G. and Wan, A. T. K. (2012). Model Averaging for Varying-Coefficient Partially Linear Measurement Error Models.*Electronic Journal of Statistics*,**6**, 1017-1039.**Wang, H.**and Sun, D. (2012). Objective Bayesian analysis of a truncated model.*Statistics and Probability Letters*,**82**, 2125-2135. pdf**Wang, H.**, Zou, G. and Wan, A. T. K. (2013). Adaptive Lasso for Varying-Coefficient Partially Linear Measurement Error Models.*Journal of Statistical Planning and Inference*,**143**, 40-54. pdf**Wang, H.**and Zhou, S. Z. F. (2013). Interval Estimation by Frequentist Model Averaging.*Communications in Statistics - Theory and Method*,**42**, 4342-4356. pdf**Wang, H.**, Pepelyshev, A. and Flournoy, N. (2013). Optimum design for a new bounded log-linear regression model.*MoDa 10 - Advances in Model-Oriented Design and Analysis*, 237-245. Springer. pdf**Wang, H.**, Flournoy, N. and Kpamegan, E. (2014). A New Bounded Log-linear Regression Model.*Metrika*,**77**, 695-720. pdf**Wang, H.**, Chen, X. and Flournoy, N. (2014). The Focus Information Criterion and Model Averaging for Varying-Coefficient Partially Linear Measurement Error Models.*Statistical Papers*,**57**, 99-113. pdf**Wang, H.**, Li, Y. and Sun, J. (2015). The Focused and Model Average Estimation for Panel Count Data.*Scandinavian Journal of Statistics*,**42**, 732-745. pdf**Wang, H.**and Flournoy, N. (2015) On the consistency of the maximum likelihood estimation for the three parameter lognormal distribution.*Statistics and Probability Letters*,**105**, 57-64. pdf- Li, Y., He, X.,
**Wang, H.**and Sun, J. (2016) Regression Analysis of Longitudinal Data with Correlated Censoring and Observation Times.*Lifetime Data Analysis*,**22**, 343-362. pdf - Li, Y., He, X.,
**Wang, H.**and Sun, J. (2015) Semiparametric Regression of Multivariate Panel Count Data with Informative Observation Times.*Journal of Multivariate Analysis*,**140**, 209-219. pdf **Wang, H.**, Schaeben, H. and Keidel, F. (2015) Optimized Subsampling for Logistic Regression with Imbalanced Large Datasets.*Proceeding of the 17th annual conference of the International Association for Mathematical Geosciences*, 1113-1119.- Mo, W,
**Wang, H.**and Jacobsa, J. (2016). Understanding the influence of climate change on the embodied energy of water supply.*Water Research*, 220-229. - Lane, A.,
**Wang, H.**and Flournoy, N. (2016) Conditional inference in two-stage response-adaptive experiments via the bootstrap*MoDa 11 - Advances in Model-Oriented Design and Analysis*, 173-181. Springer. pdf - Li, Y., He, X.,
**Wang, H.**and Sun, J. (2016) Joint Analysis of Longitudinal Data and Informative Observation Times with Time-Dependent Random Effects.*New Developments in Statistical Modeling, Inference and Application*, 37-51. - Zhang, X.,
**Wang, H.**, Ma, Y. and Carroll, R. J. (2017) Linear Model Selection when Covariates Contain Errors.*Journal of the American Statistical Association*, doi10.1080/01621459.2016.1219262. pdf Supplementary **Wang, H.**, Zhu, R. and Ma, P. (2017+) Optimal Subsampling for Large Sample Logistic Regression.*Journal of the American Statistical Association*, doi:10.1080/01621459.2017.1292914. pdf R package**Wang, H.**, Yang, M. and Stufken, J. (2017+) Information-Based Optimal Subdata Selection for Big Data Linear Regression.*Journal of the American Statistical Association*, to appear. pdf R Code

### Working Papers

- Zhu, R.,
**Wang, H.**, Zhang, X., and Liang, H. - A Scalable Frequentist Model Averaging Method.

### Teaching

**At the University of Missouri**- Statistics 1200 - Introductory Statistical Reasoning, Fall 2010, Spring 2011, Fall 2011 (3cr.)
- Statistics 2500 - Introductory to probability and statistics I, Spring 2012 (3cr.)
- Statistics 3500 - Introductory to probability and statistics II, Fall 2012, Spring 2013 (3cr.)

**At the University of New Hampshire**- Math 539 - Introduction to Statistical Analysis, Fall 2014 (4cr.)
- Math 644 - Statistics for Engineers and Scientists, Fall 2013, Spring 2014, Fall 2014 (4cr.)
- Math 736/836 - Advanced Statistical Methods for Research, Spring 2014, Spring 2015, Spring 2016 (4cr.)
- Math 739/839 - Applied Regression Analysis, Fall 2016 (4cr.)
- Math 755/855 - Probability with Applications, Fall 2015, Fall 2016 (4cr.)
- Math 756/856 - Principles of Statistical Inference, Spring 2016, 2017 (4cr.)
- Math 969 - Topics in Probability and Statistics (3cr.)

**At the University of Connecticut**- BIST/STAT 5505 - Applied Statistics I, Fall 2017 (3cr.)