Liqun Wang

Name: Liqun Wang

Position Title: Head/Professor

Office Phone Number: (204) 474-8172

Email: Liqun.Wang@UManitoba.CA

Research and Teaching Interests

Personal Website

Recent Publications

• Fan, Jun; Kong, Lingchen; Wang, Liqun and Xiu, Naihua (2018). Variable Selection in Sparse Regression with Quadratic Measurements. Statistica Sinica 28, 1157–1178.
• Zhu, Quing and et al. (2018). Identifying an early treatment window for predicting breast cancer response to neoadjuvant chemotherapy using immunohistopathology and hemoglobin parameters. Breast Cancer Research 20 (1), 56.
• Fan J, Kong L, Wang L, Xiu N. (2017). Variable selection in sparse regression with quadratic measurements. Statistica Sinica, forthcoming.
• Guan, Jing and Wang, Liqun (2017). Instrumental Variable Estimation in Linear Quantile Regression Models with Measurement Error. Chinese Journal of Applied Probability and Statistics 33 (5), 475–486.
• Jin, Zhiyong and Wang, Liqun (2017). First Passage Time for Brownian Motion and Piecewise Linear Boundaries. Methodology and Computing in Applied Probability 19, 237-253.

→ See more publications

Biography

Liqun Wang holds a Bachelor’s degree in mathematics, a Master’s degree in statistics and a Doctoral degree in statistics and econometrics. He also has a Postgraduate Diploma in mathematical and computer sciences. Liqun Wang has research and teaching experience at various universities in Europe and North-America.

Research Grants

1. Natural Sciences and Engineering Research Council of Canada (NSERC) – Discovery Grant (2016-2021): Semiparametric Efficient Inference Methods in Complex Data Models.
2. Natural Sciences and Engineering Research Council of Canada (NSERC) – Discovery Grant (2009-2015): Nonlinear Statistical Inference and Boundary Crossing Probabilities.
3. MITACS Research Award (2009-2010): Development of a Mathematical Tool for Accelerated Durability Tests of Ground Vehicles.
4. Canadian Institute of Health Research (CIHR) – Operating Grant (2008-2011): Classification Algorithms to Distinguish Chronic Disease Cases from Non-Cases in Administrative Data.
5. National Program for Complex Data Structures (NPCDS) – National Project (2007-2009): Statistical Innovation for the Analysis of Complex Data in Medical and Health Sciences.
6. Natural Sciences and Engineering Research Council of Canada (NSERC) – Discovery Grant (2004-2009): Stochastic Modeling and Simulation Based Methods.
7. National Program on Complex Data Structures (NPCDS) – National Project (2005): Current Issues in the Analysis of Incomplete Longitudinal Data.
8. Natural Sciences and Engineering Research Council of Canada (NSERC) – Research Tools & Instruments Grant (2005): High-performance Workstation for Statistical Computation.
9. Natural Sciences and Engineering Research Council of Canada (NSERC) – Discovery Grant (2000-2004): Nonlinear Systems and Simulation Methods.
10. Natural Sciences and Engineering Research Council of Canada (NSERC) – Equipment Grant (2000): Station and Server for Simulations and Statistical Applications.

Selected Publications

1. Zhu, Q. et al. (2018). Identifying an early treatment window for predicting breast cancer response to neoadjuvant chemotherapy using immunohistopathology and hemoglobin parameters. Breast Cancer Research, 20:56.
2. Fan J, Kong L, Wang L, Xiu N. (2018). Variable selection in sparse regression with quadratic measurements. Statistica Sinica, 28, 1157-1178.
3. Guan J, Wang L. (2017). Instrumental variable estimation in linear quantile regression models with measurement error. Chinese Journal of Applied Probability and Statistics 33, 475-486.
4. Jin Z, Wang L (2017). First passage time for Brownian motion and piecewise linear boundaries. Methodology and Computing in Applied Probability, 19, 237-253.
5. Fan J, Kong L, Wang L, Xiu N. (2016). The uniqueness and greedy method for quadratic compressive sensing. 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 808-815.
6. Li DH, Wang L. (2016). A weighted simulation-based estimator for incomplete longitudinal data models. Statistics & Probability Letters, 113, 16-22.
7. Jin Z, Wang L. (2015). First passage time for Brownian motion and piecewise linear boundaries. Methodology and Computing in Applied Probability, DOI 10.1007/s11009-015-9475-2.
8. Zhang S, Zheng X, Chen JM, Chen Z, Dan B, Yi X, Wang L, Wu G. (2015). A global carbon assimilation system using a modified ensemble Kalman filter, Geosci. Model Dev., 8, 805-816.
9. Xu K, Ma Y, Wang L. (2015). Instrument assisted regression for errors in variables models with binary response. Scandinavian Journal of Statistics, 42, 104-117.
10. Zhu Q, Wang L, Tannenbaum S, Ricci A Jr., DeFusco P, Hegde P. (2014). Pathologic response prediction to neoadjuvant chemotherapy utilizing pretreatment near infrared imaging parameters and tumor pathologic criteria. Breast Cancer Research, 16, 456-469.
11. Wu G, Yi X, Wang L, Liang X, Zhang S, Zhang X, Zheng X. (2014). Improving the ensemble transform Kalman filter using a second-order Taylor approximation of the nonlinear observation operator. Nonlinear Processes in Geophysics, 21, 955-970.
12. Abarin T, Li H, Wang L, Briollais L (2014) On method of moments estimation in linear mixed effects models with measurement error on covariates and response with application to a longitudinal study of gene-environment interaction. Statistics in Biosciences, 6, 1-18.
13. Wang L, Lee CH (2014). Discretization-based direct random sample generation. Computational Statistics & Data Analysis, 71, 1001-1010.
14. Li D, Wang L (2013). A semiparametric estimation approach for linear mixed models. Communications in Statistics – Theory and Methods, 42, 1982-1997.
15. Wu G, Zheng X, Wang L, Zhang S, Liang X, Li Y (2013). A new structure of error covariance matrices and their adaptive estimation in EnKF assimilation. Quarterly Journal of the Royal Meteorological Society, 139, 795-804.
16. Abarin T, Wang L (2012). Instrumental variable approach to covariate measurement error in generalized linear models. Annals of the Institute of Statistical Mathematics, 64, 475-493.
17. Li H, Wang L (2012). A consistent simulation-based estimator in generalized linear mixed models. Journal of Statistical Computation and Simulation, 82, 1085-1103.
18. Li H, Wang L (2012). Consistent estimation in generalized linear mixed models with measurement error. Journal of Biometrics and Biostatistics, S7:007. doi:10.4172/2155-6180.S7-007.
19. Chen S, Hsiao C, Wang L (2012). Measurement errors and censored structural latent variables models. Econometric Theory, 28, 696-703.
20. Wang L, Hsiao C (2011). Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models. Journal of Econometrics, 165, 30-44.
21. Abarin, T.; Wang, L. (2009). Second-order least squares estimation of censored regression models. Journal of Statistical Planning and Inference, 139, 125-135.
22. Wang, L.; Leblanc, A. (2008). Second-order nonlinear least squares estimation. Annals of the Institute of Statistical Mathematics, 60, 883-900.
23. Sadatsafavi, M.; Moayyeri, A.; Wang, L.; Leslie, W. D. (2008). Heteroscedastic regression analysis for factors affecting bone mineral density monitoring. Journal of Bone and Mineral Research, 23, 1842-1849.
24. Sadatsafavi, M.; Moayyeri, A.; Wang, L.; Leslie, W. D. (2008). Optimal decision criterion for detecting change in bone mineral density during serial monitoring: a Bayesian approach. Osteoporosis International, 19, 1589-1596.
25. Wang, L. (2007). A unified approach to estimation of nonlinear mixed effects and Berkson measurement error models. Canadian Journal of Statistics, 35, 233-248.
26. Wang, L.; Fu, J. C. (2007). A practical sampling approach for a Bayesian mixture model with unknown number of components. Statistical Papers, 48, 631-653.
27. Wang, L.; Hsiao, C. (2007). Two-stage estimation of limited dependent variable models with errors-in-variables. Econometrics Journal, 10, 426-438.
28. Wang, L.; Pötzelberger, K. (2007). Crossing probabilities for diffusion processes with piecewise continuous boundaries. Methodology and Computing in Applied Probability, 9, 21-40.
29. Leslie, W. D.; Moayyeri, A.; Sadatsafavi, M.; Wang, L. (2007). A new approach for quantifying change and test precision in bone densitometry. Journal of Clinical Densitometry, 10 (4), 365-369.
30. Abarin, T.; Wang, L. (2006). Comparison of GMM with second-order least squares estimator in nonlinear models. Far East Journal of Theoretical Statistics, 20, 179-196.
31. Wang, G. G.; Wang, L.; Shan, S. (2005). Reliability assessment using discriminative sampling and metamodeling. SAE Transactions Journal of Passenger Cars: Mechanical Systems, 114, 291-300.
32. Wang, G. G.; Wang, L.; Shan, S. (2005). Reliability assessment using discriminative sampling and metamodeling. Reliability and Robust Design in Automotive Engineering 2005, 2005-01-0349, SAE World Congress Special Publications, SAE International.
33. Xue, L.; Fu, J. C.; Wang, F.; Wang, L. (2005). A mixture model approach to analyzing major element chemistry data of the Changjiang (Yangtze River). Environmetrics, 16, 305-318.
34. Wang, L. (2004). Estimation of nonlinear models with Berkson measurement errors. Annals of Statistics, 32, 2559-2579.
35. Wang, L.; Shan, S.; Wang, G. G. (2004). Mode-pursuing sampling method for global optimization on expensive black-box functions. Engineering Optimization, 36, 419-438.
36. Wang, L. (2003). Estimation of nonlinear Berkson-type measurement error models. Statistica Sinica, 13, 1201-1210.

Conference Talks

1. Identifiability and estimation of AR-ARCH models with measurement error. The Joint Statistical Meetings, Seattle, USA, 8-13/8/2015.
2. Identifiability and estimation of AR-ARCH models with measurement error. The 2nd ICSA-Canada Chapter 2015 Symposium, Calgary, Canada, 4-6/8/2015.
3. An adaptive ensemble Kalman filter for global carbon dioxide data assimilation. The 9th ICSA International Conference, 2013.12.20-23, Hong Kong, China.
4. Semiparametric estimation in longitudinal or panel data models. International Conference on Optimization and Statistics, 2013.6.11-12, Beijing, China. (Keynote Speaker)
5. Adaptive estimation of error covariance matrices in ensemble Kalman filter for data assimilation. International Workshop on the Perspectives on High-dimensional Data Analysis III, 2013.5.23-25, Pacific Institute for Mathematical Sciences, Vancouver, Canada.
6. Second-order least squares estimation in linear dynamic panel data models. 11th Iranian Statistical Conference, 2012.8.28-30, Tehran, Iran.
7. A weighted simulation-based estimator for incomplete longitudinal data. ICSA 2011 Applied Statistics Symposium, 2011.6.26-29, New York, USA.
8. Second-order least squares estimation in dynamic panel data models. 17th International Panel Data Conference, July 8-10, 2011, Montreal, Canada.
9. Instrumental variable estimation in nonlinear models with covariate measurement error. The Eighth ICSA International Conference: Frontiers of Interdisciplinary and Methodological Statistical Research, December 19-22, 2010, Guangzhou, China.
10. Instrumental Variable Estimation in Generalized Linear and Nonlinear Semiparametric Models with Measurement Error. Biostatistics and Epidemiology – Statistical Modelling of Environmental and Health Data, August 18-20, 2010, Fredericton, New Brunswick.
11. Instrumental Variable Methods in Nonlinear Errors-in-Variables Models. The Annual Meeting of the Chinese Association of Probability and Statistics, May 1-2, 2010, Hualian, Taiwan.
12. Instrumental variable methods for nonlinear regression with mismeasured covariates. Workshop on Modelling Indirectly or Imprecisely Observed Data, 10-12/12/2009, London, Ontario, Canada.
13. Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models. 26th Annual Meeting of Canadian Econometrics Study Group, Ottawa, Canada, 19-20/9/2009.
14. Idenitfiability and estimation in nonlinear systems with errors-in-variables. Econometrics, Time Series Analysis and System Theory – A Conference in Honor of Manfred Deistler, Vienna, Austria, 18-20/6/2009.
15. Discussion on “Errors-in-variables models: a generalized functions approach” by V. Zinde-Walsh. 43rd Annual Conference of the Canadian Economics Association, 29-31/5/2009, Toronto, Canada.
16. Identifiability and estimation of nonlinear semiparametric models with measurement errors. International Conference on Nonparametric Methods for Measurement Error Models and Related Topics, Ottawa, Canada, 3-5/5/2009.
17. Boundary crossing probabilities and risk modeling and management. China-Canada Industry Workshop on Enterprise Risk Management, Wuhan, China, 26-30/11/2008.
18. Statistical inference in nonlinear systems with mismeasured covariates. 19th Annual Meeting of the International Environmetrics Society, Kelowna, British Columbia, Canada, 8-13/6/2008.
19. Understanding and managing mismeasured variables in biostatistical analysis. Short Course of The National Institute for Complex Data Structures (NICDS), Pacific Institute for Mathematical Sciences, Vancouver, Canada, 24/4/2008.
20. Second-order least squares estimation for nonlinear mixed effects models. Joint Statistical Meetings, Salt Lake City, USA, 29/7-2/8/2007.
21. First hitting time distribution for diffusion processes and time-dependent double barriers. Joint Conference of Canadian Mathematical Society (CMS) and The Mathematics of Information Technology and Complex Systems (MITACS), Winnipeg, Canada, 31/5-3/6/2007.
22. Second-order least squares estimation for nonlinear mixed effects models. Statistics Workshop, Brock University, Canada, 19/10/2006.
23. Simulation-based least squares estimation for nonlinear panel data models. 23rd Canadian Econometrics Study Group Conference, Niagara Falls, Canada, 19-21/10/2006.
24. A second-order least squares estimator for nonlinear panel data models. Econometric Society European Meeting, Vienna, Austria, 24-28/8/2006.
25. A second-order least squares estimator for nonlinear panel data models. International Symposium on Econometric Theory and Applications, Xiamen, China, 4-6/4/2006.
26. Identifiability and estimation of semiparametric nonlinear errors-in-variables models. The Joint Meeting of the Chinese Society of Probability and Statistics (CSPS) and the Institute of Mathematical Statistics (IMS), Beijing, China, 9-12/7/2005.
27. Identifiability and estimation of semiparametric errors-in-variables models. Annual Meeting of the Statistical Society of Canada, Saskatoon, Canada, 12-15/6/2005.

Links