Linglong Kong, PhD
Contact
Professor, Canada Research Chair in Statistical Laerning, and Canada CIFAR AI Chair, Faculty of Science - Mathematics & Statistical Sciences
- lkong@ualberta.ca
Overview
Research
Research Areas
Functional and Neuroimaging data analysis, Robust statistics and quantile regression, Statistical machine learning, and AI in smart health.
Courses
STAT 512 - Techniques of Mathematics for Statistics
Introduction to mathematical techniques commonly used in theoretical Statistics, with applications. Applications of diagonalization results for real symmetric matrices, and of continuity, differentiation, Riemann-Stieltjes integration and multivariable calculus to the theory of Statistics including least squares estimation, generating functions, distribution theory. Prerequisite: consent of Department.
STAT 561 - Sample Survey Methodology
Review of basic sampling schemes: simple random sampling, and stratified random sampling, and systematic sampling. Multistage sampling schemes. Estimation of nonlinear parameters: ratios, regression coefficients, and correlation coefficients. Variance estimation techniques: linearization, BRR, jackknife, and bootstrap. Selected topics: model-based estimation, regression analysis from complex survey data. Relevant computer packages. Prerequisites: STAT 361, 372, 471.
Featured Publications
Comment on "Measuring Housing Vitality from Multi-source Big Data and Machine Learning"
Tu, W., Jiang, B., and Kong, L.
Journal of the American Statistical Association. 2022 October; 117 (539):1060-1062
High-dimensional spatial quantile function-on-scalar regression
Z Zhang, X Wang, L Kong, H Zhu
Journal of the American Statistical Association. 2022 July; 117 (539):1563-1578
A General Framework for Quantile Estimation with Incomplete Data
Han, P., Kong, L., Zhao, J., and Zhou, X.
Journal of Royal Statistical Society: Series B. 2019 October; 81 (2):305-333
Model-Robust Designs for Quantile Regression
Kong, L. and Wiens, D.
Journal of the American Statistical Association. 2015 January; 110 (507):233-245
Multivariate Varying Coefficient Models for Functional Responses
Zhu, H., Li, R., and Kong, L.
Annals of Statistics. 2014 June; 40 (5):2634-2666
Spatially Varying Coefficient Model for Neuroimaging Data with Jump Discontinuities
Zhu, H., Fan, J., and Kong, L.
Journal of the American Statistical Association. 2012 August; 109 (507):1084-1098
Discussion of "Multivariate Quantiles and Multiple- Output Regression Quantiles: From L1 Optimization to Halfspace Depth"
Kong, L. and Mizera, I.
Annals of Statistics. 2010 November; 38 (2):685-693