Prof. Longhai Li

Home Teaching Research Students Publications Software

Professor Department of Mathematics and Statistics University of Saskatchewan 106 Wiggins Road, MCLN 219 Saskatoon, SK, CANADA, S7N5E6 Email: longhai.li@usask.ca Homepage: https://longhaisk.github.io Profile at USASK Short Biography Contacts

Research Interest

Statistical machine learning, survival analysis, model checking, residual diagnostics

My Publications in Public Archives

Selected Papers and R Packages

• Z-residual: Computing Z-residual for survival models and generalized linear models. (under development) A demonstration for checking covariate functional forms, Github page.
• HTLR: Fitting Bayesian Logistic Regression with Heavy-tailed (Hyper-Lasso) Priors, [CRAN page], [Github page].
• NRSP: Computing NRSP residuals (Z-residuals) for survreg and coxph objects, the page for downloading
  
• Wu, T., Feng, C., Li, L. (2024). Cross-validatory Z-Residual for Diagnosing Shared Frailty Models. The American Statistician 0, 1–17. [PDF]; [Free Reprints]; [slides]; [Z-residual on Github]; [Demo]
• Wu, T., Li, L., Feng, C. (2024). Z-residual diagnostic tool for assessing covariate functional form in shared frailty models. Journal of Applied Statistics 0, 1–31. [PDF]; [Z-residual on Github]; [Demo] [slides]
• Li, L., Wu, T., Feng, C. (2021). Model diagnostics for censored regression via randomized survival probabilities. Statistics in Medicine 40, 1482–1497. [PDF]; [R Functions and Demonstration]; [slides];
• Feng, C., Li, L., Sadeghpour, A. (2020). A comparison of residual diagnosis tools for diagnosing regression models for count data. BMC Medical Research Methodology. 20(1):175.
• Dong, M., Li, L., Chen, M., Kusalik, A., Xu, W. (2020). Predictive analysis methods for human microbiome data with application to Parkinson's disease. PLOS ONE 15(8):e0237779.
• Jiang, L., Greenwood, CMT, Yao, W., Li, L. (2020). Bayesian Hyper-LASSO Classification for Feature Selection with Application to Endometrial Cancer RNA-seq Data. Scientific Reports 10(1):9747.
• Li, L., Qiu, S., Zhang, B., and Feng, C.X. (2016). Approximating Cross-validatory Predictive Evaluation in Bayesian Latent Variables Models with Integrated IS and WAIC, Statistics and Computing, 26(4), 881-897. [PDF]; [slides].
• Yao, W. and Li, L. (2014). A New Regression Model: Modal Linear Regression. Scandinavian Journal of Statistics, 41(3), 656-671. [PDF].
• Li, L. (2012). Bias-corrected Hierarchical Bayesian Classification with a Selected Subset of High-dimensional Features. Journal of American Statistical Association, 107:497, 120-134. [PDF]; [software]; [slides].