Publications

Papers & Book Chapters

Books

Google Scholar

arXiv Papers

2025

[Authors marked with * conducted the work during their PhD studies under my supervision.]

Gu. Z.*, Yu, S., Wang, G. and Wang, L. (2025+). Boosting AI-generated biomedical images with confidence through advanced statistical inference. Journal of the American Statistical Association, Theory and Methods. Special Issue on Statistical Science in AI. Forthcoming. DOI: 10.1080/01621459.2025.2552510 [Read PDF]
Kim, M.*, Wang, L. and Wang, H. (2025+). Estimation and inference of quantile spatially varying coefficient models over complicated domains. Journal of the American Statistical Association, Theory and Methods. Forthcoming. DOI: 10.1080/01621459.2025.2480867 [Read PDF] [Code]
Long, Y.*, Cao, G., Kepplinger, D. and Wang, L. (2025+). Robust mean signal estimation and inference for imaging data. Statistica Sinica. Forthcoming. [Yang Long won runner-up of the Statistical Methods in Imaging Conference 2025 Student Paper Competition]
Gu. Z.*, Li, X., Wang, G. and Wang, L. (2025+). Spatiotemporal heterogeneity learning: Generalized spatiotemporal semi-varying coefficient models with structure identification. Journal of Time Series Analysis. Forthcoming.
Das, K.*, Yu, S., Wang, G. and Wang, L. (2025). Nonparametric density estimation for scattered spatial data on irregular domains: A likelihood-based approach using bivariate penalized spline smoothing. Journal of Nonparametric Statistics. Forthcoming. [Read PDF] [Supplemental]
Gu. Z.*, Yu, S., Wang, G., Lai, M. J. and Wang, L. (2025). TSSS: A novel triangulated spherical spline smoothing for surface-based imaging. Journal of Nonparametric Statistics, 37(3), 683-712. DOI: 10.1080/10485252.2025.2449886 [Read PDF] [Supplemental] [Zhiling Gu won runner-up of the Statistical Methods in Imaging Conference 2023 Student Paper Competition]
Wang, G., Wang, Y.*, Gao, A. and Wang, L. (2025). Efficient nonparametric estimation of 3D point cloud signals through distributed learning. Journal of Computational and Graphical Statistics, 34(2), 746-758. [Read PDF] [Supplemental]
Wang, Y.*, Wang, G., Klinedinst, B., Willette, A. and Wang, L. (2025). Statistical inference for mean functions of complex 3D objects. Statistica Sinica, 35, 1-25. DOI: 10.5705/ss.202023.0071 [Read PDF]
Hong, Y.A., Shen, K., Han, H.R., Hepburn, K., Wang, L., Lu, H.K., Park, V.T. and Chi, I. (2025). Two-year follow-up of Dementia caregivers after a digital health intervention WECARE: A mixed-method study. Aging & Mental Health, 29(4), 631-638.
Yu, S., Wang, G. and Wang, L. (2025). Distributed heterogeneity learning for generalized partially linear models with spatially varying coefficients. Journal of the American Statistical Association, Theory and Methods, 120(550), 779-793. [Read PDF] [Code]

2024

[Authors marked with * conducted the work during their PhD studies under my supervision.]

Li, X., Yu, S., Wang, Y.*, Wang, G., Wang, L. and Lai, M. J. (2024). Nonparametric regression for 3D point cloud learning. Journal of Machine Learning Research, 25(102):1–56. [Read PDF]
Wang, L., Wang, G. and Gao, A. (2024). Exploring heterogeneity and dynamics of meteorological influences on US PM2.5: A distributed learning approach with spatiotemporal varying coefficient models. Spatial Statistics, 61, 100826 [Read PDF]
Li, X., Freeman, N. and Wang, L. (2024). Q-Learning Based Methods for Dynamic Treatment Regimes. In Zhao, Y. and Chen, D. (Eds.). Precision Health: Theory, Methods and Applications. Springer Nature.
Kuhlmann, D., Rongerude, J., Das, B. and Wang, L. (2024). Rental property owner stress during the Covid-19 pandemic: Results from a Minneapolis, MN survey. Housing and Society, 51(1), 4–33. DOI: 10.1080/08882746.2023.2227541 [Read PDF]
Velma, K. L., et al. (2024). Challenges of COVID-19 case forecasting in the US, 2020-2021. PLOS Computational Biology, 20(5): e1011200.

2023

[Authors marked with * conducted the work during their PhD studies under my supervision.]

Yu, S.*, Kusmec, A., Wang, L. and Nettleton, D. (2023). Sparse modeling of functional linear regression via fused lasso with application to genotype-by-environment Interaction studies. Journal of Agricultural, Biological and Environmental Statistics, 28, 401–422. DOI: 10.1007/s13253-023-00529-2 [Read PDF]
Wang, G., Gu, Z.*, Li, X.*, Yu, S.*, Kim, M.*, Wang, Y.*, Gao, L. and Wang, L. (2023). Comparing and integrating US COVID-19 data from multiple sources with anomaly detection and repairing. Journal of Applied Statistics, 50, 2408–2434. DOI: 10.1080/02664763.2021.1928016. [Read PDF]
Kuhlmann, D., Rongerude, J., Wang, L. and Wang, G. (2023). A Statistical Machine Learning Approach to Identify Rental Properties from Public Data Sources. Cityscape, 25 (2), 367–378. [Read PDF]

2022

[Authors marked with * conducted the work during their PhD studies under my supervision.]

Yu, S.*, Wang, Y.*, Wang, L. and Gao, L. (2022). Spatiotemporal autoregressive partially linear varying coefficient models. Statistica Sinica, 32, 2119-2146. DOI:10.5705/ss.202020.0383 [Read PDF]
Wang, Y.*, Kim, M.*, Yu, S.*, Li, X., Wang, G. and Wang, L. (2022). Nonparametric estimation and inference for spatiotemporal epidemic models. Journal of Nonparametric Statistics, 34 (3), 683-705. DOI: 10.1080/10485252.2021.1988084 [Read PDF]
Cramer, E. Y., et al. (2022). Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US. Proceedings of the National Academy of Sciences, 119 (15), e2113561119. [Read PDF]
Zhang, T., Zhou, Y., Wang, L., Zhao, K. and Zhu, Z. (2022). Estimating 1 km gridded daily air temperature using a spatially varying coefficient model with sign preservation. Remote Sensing of Environment, 277, 113072. [Read PDF]
Zhang, T., Zhou, Y., Zhao, K., Zhu, Z., Chen, G., Hu, J., and Wang, L. (2022). A global dataset of daily near-surface air temperature at 1-km resolution (2003–2020). Earth System Science Data, 14, 5637–5649. DOI: 10.5194/essd-14-5637-2022 [Read PDF].

2021

[Authors marked with * conducted the work during their PhD studies under my supervision.]

Li, X.*, Wang, L. and Wang, H. (2021). Sparse learning and structure identification for ultra-high-dimensional image-on-scalar regression. Journal of the American Statistical Association, Theory and Methods, 116, 1994-2008. [Read PDF]
Kim, M.*, Gu, Z.*, Yu, S.*, Wang, G., and Wang, L. (2021). Methods, challenges, and practical issues of COVID-19 projection: a data science perspective. Journal of Data Science,19 (2), 219-242. [Read PDF] [Philosophy of Data Science]
Wang, L., Wang, G., Li, X., Yu, S.*, Kim, M.*, Wang, Y.*, Gu, Z.* and Gao, L. (2021). Modeling and forecasting COVID-19. AMS: Notices Of The American Mathematical Society, 68, 585-595. [Read PDF]
Kim, M.*, Wang, L. and Zhou, Y. (2021). Spatially varying coefficient models with sign preservation of the coefficient functions. Journal of Agricultural, Biological, and Environmental Statistics, 26, 367-386 [Read PDF]
Yu, S.*, Wang, G. and Wang, L. (2021). Discussion of "Evaluate the risk of resumption of business for the states of New York, New Jersey and Connecticut via a pre-symptomatic and asymptomatic transmission model of COVID-19". Journal of Data Science. [Read PDF]
Yu, S.*, Wang, G., Wang, L. and Yang, L. (2021). Multivariate spline estimation and inference for image-on-scalar regression. Statistica Sinica, 31, 1463-1487. [Read PDF] [An early version was selected as one of three runners-up of 2019 ASA Statistics in Imaging Section Student Paper Competition]
Kim, M.* and Wang, L. (2021). Generalized spatially varying coefficient models. Journal of Computational and Graphical Statistics, 30, 1-10. [Read PDF]

2020

Wang, Y.*, Wang, G.*, Wang, L. and Ogden, T. (2020). Simultaneous confidence corridors for mean functions in functional data analysis of imaging data. Biometrics, 76, 427-437. [Read PDF] & R package
Yu, S.*, Wang, G.*, Wang, L., Liu, C.* and Yang, L. (2019). Estimation and inference for generalized geoadditive models. Journal of the American Statistical Association, Theory and Methods, 115, 761-774. [Read PDF] & R package
Wang, L., Wang, G.*, Lai, M. J. and Gao, L. (2020). Efficient estimation of partially linear models for data on complicated domains by bivariate penalized splines over triangulations. Statistica Sinica, 30, 347-369. [Read PDF] & R package
Klinedinst, B.S., Le, S.T., Larsen, B., Pappas, C., Hoth, N.J., Pollpeter, A., Wang, Q., Wang, Y.*, Yu, S.*, Wang, L., Allenspach, K., Mochel, J.P., Bennett, D.A. and Willette, A.A. (2020). Genetic factors of Alzheimer’s disease modulate how diet is associated with long-term cognitive trajectories: A UK Biobank Study. Journal of Alzheimer’s Disease, 78, 1245-1257. [Read PDF]
Cao, G., Wang, S. and Wang, L. (2020). Estimation and inference for functional linear regression models with partially varying regression coefficients. Stat, 9, e286 [Read PDF]
Klinedinst, B.S., Meierc, N.F., Larsen, B., Wang, Y.*, Yu, S.*, Mocheld, J.P., Scott, L., Wolff, T., Pollpeterg, A., Pappas, C., Wang, Q., Allenspach, K., Wang, L., Russelli, D., Bennett, D.A., Willette, A.A. (2020). Walking in the light: How history of physical activity, sunlight, and vitamin D account for body fat -- a UK Biobank study. Obesity, 28, 1428-1437. [Read PDF]
Wang, J., Cao, G., Wang, L. and Yang, L. (2020). Simultaneous confidence band for stationary covariance function of dense functional data. Journal of Multivariate Analysis. 176. [Read PDF]
Mu, J., Wang, G. and Wang, L. (2020). Efficient estimation and model identification for spatially varying coefficient autoregressive models. Journal of Nonparametric Statistics, 32, 428-451. [Read PDF]

2019

Klinedinst, B., Pappas, C., Le, S., Yu, S.*, Wang, Q., Wang, L., Allenspach, K., Mochel, J. and Willette, A. (2019). Aging-related changes in fluid intelligence, muscle and adipose mass, and sex-specific immunologic mediation: a longitudinal UK Biobank study. Brain, Behavior, and Immunity, 82, 396-405. Read PDF
Li, X.*, Wang, L. and Nettleton, D. (2019a). Additive partially linear models for ultra-high-dimensional regression. Stat, 8. e223. Read PDF
Li, X.*, Wang, L. and Nettleton, D. (2019b). Sparse model identification and learning for ultra-high-dimensional additive partially linear models. Journal of Multivariate Analysis, 173, 204-228. Read PDF
Song, X., Wang, L., Ma, S. and Huang, H. (2019). Variable selection for partially linear proportional hazards model with covariate measurement error. Journal of Nonparametric Statistics, 31, 196-220. Read PDF

2017-2018

Datta, G. S., Delaigle, A., Hall, P. and Wang, L. (2018). Semi-parametric prediction intervals in small areas when auxiliary data are measured with error. Statistica Sinica, 28, 2309-2335. Read PDF
Cao, G. and Wang, L. (2018). Simultaneous inference for the mean of repeated functional data. Journal of Multivariate Analysis, 165, 279-295. Read PDF
Wang, L. and Cao, G. (2018). Efficient estimation for generalized partially linear single-index models. Bernoulli, 24, 1101-1127. Read PDF
Mu, J.*, Wang, G.* and Wang, L. (2018). Estimation and inference in spatially varying coefficient models. Environmetrics, 29:e2485. Read PDF & R package
Yin, S., Zhu, Z., Wang, L., Liu, B., Xie, Y., Wang, G.* and Li, Y. (2018). Regional soil erosion assessment based on a sample survey and geostatistics. Hydrology and Earth System Sciences, 22, 1695-1712. Read PDF
Song, X. and Wang, L. (2017). Partially time-varying coefficient proportional hazards models with error-prone time-dependent covariates: an application to the AIDS Clinical Trials Group 175 Data. Annals of Applied Statistics, 11, 274-296. Read PDF

2015-2016

Cao, G., Wang, L., Li, Y. and Yang, L. (2016). Oracle-efficient confidence envelopes for covariance functions in dense functional data. Statistica Sinica, 26, 359-383. Read PDF
Wang, G.* and Wang, L. (2015). Spline estimation and variable selection for single-index prediction models with a diverging number of index parameters. Journal of Statistical Planning and Inference, 162, 1-19. Read PDF

2013-2014

Wang, L., Wang, S. and Wang, G.* (2014). Variable selection and estimation for longitudinal survey data. Journal of Multivariate Analysis, 130, 409-424. Read PDF
Gu, L., Wang, L., Hardle, W. and Yang, L. (2014). Simultaneous confidence corridor for varying coefficient regression with sparse functional data. Test, 23, 806-843. Read PDF
Wang, L., Xue, L., Qu, A. and Liang, H. (2014). Estimation and model selection in generalized additive partial linear models for correlated data with a diverging number of covariates. The Annals of Statistics, 42, 592-624. Read PDF
Lai, M. J. and Wang, L. (2013). Bivariate penalized splines for regression. Statistica Sinica, 23, 1399-1417. Read PDF & R package & Blog introduction
Ma, S., Song, Q. and Wang, L. (2013). Simultaneous variable selection and estimation in semiparametric modeling of longitudinal/clustered data. Bernoulli, 19, 252-274. Read PDF

2011-2012

Cao, G., Wang, J., Wang, L. and Todem, D. (2012). Spline confidence bands for functional derivatives. Journal of Statistical Planning and Inference, 142, 1557-1570. Read PDF
Wang, L., Feng, C.*, Song, Q., Yang, L. (2012). Efficient semiparametric GARCH modeling of financial volatility. Statistica Sinica, 22, 249-270. Read PDF
Wang, L., Liu X., Liang, H. and Carroll, R. J. (2011). Estimation and variable selection for generalized additive partial linear models. The Annals of Statistics, 39, 1827-1851. Read PDF
Wang, L. and Wang, S. (2011). Nonparametric additive model-assisted estimation for survey data. Journal of Multivariate Analysis, 102, 1126-1140. Read PDF
Wang, L. (2011). A nonparametric analysis of environmental Kutznets curves. Environmetrics, 22, 420-430. Read PDF
Liu, X., Wang, L. and Liang, H. (2011). Estimation and variable selection for semiparametric additive partial linear models. Statistica Sinica, 21, 1225-1248. Read PDF
Gao, L. and Wang, L. (2011). Security price responses to unexpected earnings: a nonparametric investigation. Statistical Methods and Applications, 20, 241-258. Read PDF

2009-2010

Wang, L. and Yang, L. (2010). Simultaneous confidence bands for time series prediction function. Journal of Nonparametric Statistics, 22, 999-1018. Read PDF
Wang, L. (2009). Single-index model-assisted estimation in survey sampling. Journal of Nonparametric Statistics, 21, 487-504. Read PDF
Wang, L. and Yang, L. (2009). Spline estimation of single-index models. Statistica Sinica, 19, 765-783. Read PDF

Before 2010

Huang X., Wang, L., Yang, L. and Kravchenko, A. N. (2008). Management practice effects on relationships of grain yields with topography and precipitation. Agronomy Journal, 100, 1463-1471. Read PDF
Wang, L. and Yang, L. (2007). Spline-backfitted kernel smoothing of nonlinear additive autoregression model. The Annals of Statistics, 35, 2474-2503. Read PDF

Wang, L. and Liang, H. (2004). Strong uniform convergence for the improved estimator of the regression function under phi-mixing conditions. Metrika, 59, 245-261. Read PDF
Liang, H. and Wang, L. (2001). Convergence rates in the law of large numbers for B-valued random elements. Acta Mathematica Scientia, Series B, 21, 229-236. Read PDF

arXiv Papers

Li, X., Yu, S., Wang, Y., Wang, G. and Wang, L. (2021). Spline smoothing of 3D geometric data. [arXiv:2106.04255]
Yu, S., Wang, L., Wang, G. and Yang, L. (2021). Multivariate spline estimation and inference for image-on-scalar regression. [arXiv:2106.01431]
Wang, Y., Wang, G., Wang, L. and Ogden, T. (2020). Simultaneous confidence corridors for mean functions in functional data analysis of imaging data. [arXiv:2106.01431]
Wang, L., Wang, G., Gao, L., Li, X., Yu, S. Kim, M., Wang, Y. and Gu, Z. (2020). Spatiotemporal dynamics, nowcasting and forecasting of COVID-19 in the United States. [arXiv:2004.14103] Supplementary Materials.
Wang, J., Cao, G., Wang, L. and Yang, L. (2019). Simultaneous confidence band for stationary covariance function of dense functional
data. [arXiv:1903.05522]
Li, X., Wang, L. and Nettleton, D. (2018). Sparse model identification and learning for ultra-high-dimensional additive partially linear models. [arXiv:1811.00488]
Wang, L., Wang, G., Lai, M. J. and Gao, L. (2016). Efficient estimation of partially linear models for spatial data over complex domains. [arXiv:1605.08737]
Wang, L. and Wang, S. (2011). Nonparametric additive model-assisted estimation for survey data. [arXiv:1101.0831]
Wang, L. (2009). Single-index model-assisted estimation in survey sampling. Manuscript. Read Full Version
Wang, L. and Yang, L. (2007a). Spline single-index prediction model. [arXiv:0704.0302]
Wang, L. and Yang, L. (2007b). Spline-backfitted kernel smoothing of nonlinear additive autoregression model. [arXiv:math/0612677]

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