Mei-Ling Huang

Professor of Mathematics

mei-ling huang

PhD, MSc, (Windsor)

Office: Mackenzie Chown J411
905 688 5550 x4255
mhuang@brocku.ca

  • Nonparametric Statistical Inference Theory and Methods;
  • Extreme value Theory and its Applications.
  • Quantile Regression Theory and Applications.
  • Experimental Design and Regression Theory and Methods;
  • Applied Probability, Stochastic Models and Queueing Theory;
  • Survival Analysis and Risk models;
  • Probability Distribution Theory and Limit theory;
  • Monte Carlo Simulations and Resampling techniques.

Representative Articles in Refereed Journals :

Huang, M. L. and *Nguyen, C. (2018). “A Nonparametric Approach on Quantile Regression”, Journal of Statistical Distributions and Applications. Volume 5, Issue 3, pp.1-14. https://doi.org/10.1186/s40488-018-0084-9.

Huang, M. L., Kerman, R. and *Spector, S. (2018). “An Estimate of the Root Mean Square Error Incurred when Approximating an f ∈ L2() by a Partial Sum of its Hermite Series”, Mathematics, 2018 Volume 6, Issue 64, pp.64-82, https://doi.org/10.3390/math6040064.

Huang, M. L. and *Rat, R. (2017). “A New Weighted Quantile Regression”, Cogent Mathematics (2017), 4: 1357237, pp. 1-19. https://doi.org/10.1080/23311835.2017.1357237.

Huang, M. L. and *Nguyen, C. (2017). “High Quantile Regression for Extreme Events”, Journal of Statistical Distributions and Applications Volume 4, Issue 1, Article 4, pp.1-20, https://doi.org/10.1186/s40488-017-0058-3.

Huang, M. L., Xu, X., and Tashnev, D. (2015). “A Weighted Quantile Linear Regression”, Journal of statistical Computation and Simulation Volume 85, No. 13, pp. 2596-2618.

Ha, H., Huang, M. L., and Li, D. (2014). “A Remark on Strong Law of Large Number for Weighted U-Statistics”, Acta Mathematica Sinica, Volume 30, No. 9, 1595-1605.

Coia, V. and Huang, M. L. (2014). “A Sieve Model for Extreme Values”, Journal of Statistical Computation and Simulation, Volume 84, No. 8, pp. 1692-1710.

Fajardo, V. A. and Huang, M. L. (2014). “A Least Square Method on Confidence Regions for High Quantile of Heavy Tailed Distributions”, Advances and Applications in Statistics, Volume 38, Number 2, pp. 81-111.

Huang, M. L. and Zhao, K. (2013). “Weighted EfficientEstimation for Risk Models”, ISRN Probability and Statistics, Volume 2013, pp. 1-12.

Huang, M. L., Coia, V., and Brill, P. H. (2013). “A Cluster Truncated Pareto Distribution and its applications”, ISRN Probability and Statistics, Volume 2013, pp. 1-10.

Huang, M. L., Yuen, W. K., and *hang, M. (2013). “Efficient Methods on Confidence Intervals of Prediction Intervals”,Advances and Applications in Statistics, Volume 33, No. 1, pp.1-21.

Yu, K., Huang, M. L., and Brill, P. H. (2012). “An Algorithm for Fitting Heavy-Tailed Distributions with Generalized Hyperexponentials”, INFORMS Journal on Computing,Volume 24, No. 1, pp. 42-52.

Huang, M. L. (2011). “Optimal Estimation for the Pareto Distribution”, Journal of Statistical Computation and Simulation, Volume 81, No. 12, pp. 2059-2076.

Huang, M. L. and Zhao, K. (2010). “On Estimation of the Truncated Pareto Distribution”, Advances and Applications in Statistics, Volume 16, No. 1, pp. 83-102.

Huang, M. L. (2010). “An Efficient Estimation Method for the Pareto Distribution”, Journal of Statistics,  Advances in Theory and Applications, Volume 3, No. 1, pp. 61-78.

Huang, M. L. and Yuen, W. K. (2010). “A Bivariate Density Estimation Method based on Level Crossings”, Statistics, a Journal of Theoretical and Applied Statistics, Volume 44, No. 1, pp.31-55.

Kerman, R., Huang, M. L., and Brannan, M. (2009). “Error Estimates for Dominici’s Hermite Function Asymptotic Formula and Some Applications”, The ANZIAM Journal,Volume 50, pp.550-561.

Yuen, W. K. and Huang, M. L. (2009). “A Weighted Bivariate Density Estimation Method”, Advances and Applications in Statistics, Volume 13, No.  2, pp. 181-191.

Brill, P. H., Huang, M. L., and Hlynka, M. (2009). “A Note on an <s, S> Inventory System with Decay”, IAENG International Journal of Applied Mathematics, Volume 39, Issue 3, pp. 171-174.

Huang, M. L. (2008). “A Weighted Estimation Method for the Survival Function”, Applied Mathematical Sciences, Volume2, No. 16, pp. 753-762.

Huang, M. L. Pollanen, M., and Yuen, W. K. (2007). “An Efficient Randomized Quasi Monte-Carlo Method for the Pareto Distribution”, Monte Carlo Methods and Applications, 13(1), pp. 1-20.

Huang, M. L. (2007). “A Quantile-Score Test for Experimental Design”, Applied Mathematical Sciences, Volume 1, No. 11, pp. 507-516.

Huang, M. L. (2006). “The D-Stirling Numbers”, International Mathematical Forum, Journal for Theory and Applications,Volume 1, No. 17 – 20,  pp. 867-884.

Huang, M. L. and Brill, P. H. (2004).  “A Level Crossing Distribution Estimation Method”, Journal of Statistical Planning and Inference, Volume 124, Number 1,  pp. 45-62.

Huang, M. L. (2003). “The Efficiencies of the Estimators for the D Distribution”, The International Mathematical Journal, Volume 4, Number 3, pp. 265-280.

Huang, M. L.(2003). “The Risks of the Estimators for the R Distribution”, The International Mathematical Journal,Volume 3, Number 8, pp. 851-862.

Huang, M. L. (2002), “The R Numbers and a Restricted Occupancy Model”, The International Mathematics Journal, Volume 1, Number 3, pp. 211-222.

Huang, M. L. (2001). “On a Distribution-Free Quantile Estimator”, Computational Statistics & Data Analysis,Volume 37, Number 4, pp. 477-486.

Huang, M. L. and Brill, P. H. (2001). “On Estimation of M/G/c/c Queues”, International Transactions in Operational Research, Volume 8, Number 6, pp. 647-657.

Huang, M. L. and Brill, P. H. (2001). “A Nonparametric Regression Method”, Nonlinear Analysis, Theory, Methods and Applications, Volume 47, Number 3,  pp. 1467-1475.

Li, D., Huang, M. L., and Rosalsky, A. (2000). “Strong Invariance Principle for Arrays”, Bulletin of the Institute of Mathematics Academia Sinica, Volume 28, Number 3, pp. 167-181.

Huang, M. L. and Brill, P. H. (1999). “A Level Crossing Quantile Estimation Method”, Statistics and Probability Letters,Volume 45, Number 4, pp. 111-119.

Li, D. and Huang, M. L. (1998). “A Note on Moments of the Maximum of Cesàro Summation”, Statistics and Probability Letters, Volume 38, Number 1, pp. 73-81.

Huang, M. L., Kerman, R. A., and Weit, Y. (1997). “Abel Summability of the Autoregressive Series for the Best Linear Least Squares Predictor”, Illinois Journal of Mathematics, Volume 41, Number 3, pp. 557-587.

Huang, M. L. and Fung, K. Y. (1997). “On Moments and Cumulants of the D Compound Poisson Distribution”,Statistical Papers, Volume 38, Number 3, pp. 357-361.

Huang, M. L. and Brill, P. H. (1997). “A Level Crossing Density Estimation Method”, Nonlinear Analysis, Theory, Methods and Applications, Volume 30, Number 7, pp. 4403-4414.

Huang, M. L. and Fung, K. Y. (1993). “The D Compound Poisson Distribution”,  Statistische Hefte, Volume 34,  pp. 319-338.

Huang, M. L. and Fung, K. Y. (1993). “The D Distribution and its Applications”, Statistische Hefte, Volume 34, pp. 143-159.

Huang, M. L. and Brill, P. H. (1991). “Recurrence Relation for the Minimum Variance Unbiased Estimator for the Probability Function of the R Distribution”,Communications in Statistics, Theory and  Methods,Volume 20,  Number 12,  pp. 4005-4019.

Huang, M. L. (1990). “Recurrence Relation for the R Distribution”, Communications in Statistics, Theory and Methods, Volume 19, Number 1, pp. 145-154, 1990.

Huang, M. L. and Fung, K. Y. (1989). “The R Distribution and its Applications”, Communications in Statistics, Simulations and Computations, Volume 18, Number 1, pp. 99-119.

Huang, M. L. and Fung, K. Y. (1989). “Intervened Truncated Poisson Distribution”, Sankhya, Series B, Volume 51,  pp. 302-310.

Huang, M. L. and Fung, K. Y. (1988). “A More Generalized Stirling Distribution of the Second Kind”, Communications in Statistics, Theory and Methods, Volume 17, Number12,  pp. 4337-4356.

Huang, M. L. (1984). “Mathematical Methods for Minimal Cost Movement of Repairmen”, Railway Science Journal,Volume 3, pp. 24-27.

Huang, M. L. (1983). “Frequency Analysis in Truncated Samples”, Journal of China Railway Society, Volume 5, Number 4, pp. 62-75.

  • MATH 3P81 Experimental Design
  • MATH 3P82 Regression Analysis
  • MATH 4P81/5P81 Sampling Theory
  • MATH 4P82/5P82 Nonparametric Statistics