Publications
Manuscripts
Dai, X. and Li, L. (2021+). Orthogonal statistical inference for multimodal data analysis.
Lee, K.Y., Li, L., and Li, B.(2021+). Functional directed acyclic graphs.
Lee, K.Y., Li, L., Li, B., and Zhao, H. (2021+). Nonparametric functional graphical modeling through functional additive regression operator.
Li, L., Shi, C., Guo, T., and Jagust, W.J. (2021+). Sequential pathway inference for multimodal neuroimaging analysis.
Li, L., Zeng, J., and Zhang, X. (2021+). Generalized liquid association analysis for multimodal neuroimaging.
Lyu, X., Kang, J., and Li, L. (2021+). Statistical inference for highdimensional vector autoregression with measurement error.
Shi, C., Xu, T., Bergsma, W., and Li, L. (2021+). Double generative adversarial networks for conditional independence testing.
Shi, C., Zhou, Y., and Li, L. (2021+). Testing directed acyclic graph via structural, supervised and generative adversarial learning.
Zhang, J., Sun, W.W., and Li, L. (2021+). Generalized connectivity matrix response regression and its statistical properties.
Zhang, D., Li, L., Sripada, C., and Kang, J. (2021+). Imageonscalar regression via deep neural networks.
2021–present
Dai, X. and Li, L. (2021+). Kernel ordinary differential equations. Journal of the American Statistical Association, accepted.
Shi, C. and Li, L. (2021+). Testing mediation effects using logic of Boolean matrices. Journal of the American Statistical Association, accepted.
Tang, X. and Li, L. (2021+). Multivariate temporal point process regression. Journal of the American Statistical Association, accepted.
Lee, K.Y. and Li, L. (2021+). Functional structural equation model. Journal of the Royal Statistical Society, Series B., accepted.
Lee, K.Y. and Li, L. (2021+). Functional sufficient dimension reduction through average Frechet derivatives. The Annals of Statistics, accepted.
Lee, K.Y., Ji, D., Li, L., Constable, T., and Zhao, H. (2021+). Conditional functional graphical models. Journal of the American Statistical Association, accepted.
Li, Q. and Li, L. (2021+). Integrative factor regression and its inference for multimodal data analysis. Journal of the American Statistical Association, accepted.
Zhou, J., Sun, W.W., Zhang, J., and Li, L. (2021+). Partially observed dynamic tensor response regression. Journal of the American Statistical Association, accepted.
Xia, Y. and Li, L. (2021+). Hypothesis testing for network data with power enhancement. Statistica Sinica, accepted.
Zhao, Y., Li, L., and Caffo, B.S. (2021+). Multimodal neuroimaging data integration and pathway analysis. Biometrics, accepted.
Liu, Y., Li, L., and Wang X. (2021+). A nonlinear sparse neural ODE model for multiple functional processes. The Canadian Journal of Statistics, accepted.
Sun, W.W., Hao, B., and Li, L. (2021). Tensor data analysis. Wiley StatsRef: Statistics Reference Online, 126.
Wang, Y.R., Li, L., Li, J.J. and Huang, H. (2021). Network modeling in biology: statistical methods for gene and brain networks. Statistical Science, 36, 89108.
Ye, Y., Xia, Y., and Li, L. (2021). Paired test of matrix graphs and brain connectivity analysis. Biostatistics, 22, 402420.
2016–2020
Xia, Y., Li, L., Lockhart, S.N., and Jagust, W.J. (2020). Simultaneous covariance inference for multimodal integrative analysis. Journal of the American Statistical Association, 115, 12791291.
Zhang, J., Sun, W.W., and Li, L. (2020). Mixedeffect timevarying stochastic blockmodel and application in brain connectivity analysis. Journal of the American Statistical Association, 115, 20222036.
Kim, K., Li, B., Yu, Z., and Li, L. (2020). On post dimension reduction statistical inference. The Annals of Statistics, 48, 15671592.
Wang, M., and Li, L. (2020). Learning from binary multiway data: probabilistic tensor decomposition and its statistical optimality. Journal of Machine Learning Research, 21, 138.
Guo, X., Li, L., and Wu, Q. (2020). Modeling interactive components by coordinate kernel polynomial models. Mathematical Foundations of Computing, 3, 263277.
Sun, W.W., and Li, L. (2019). Dynamic tensor clustering. Journal of the American Statistical Association, 114, 18941907.
Wang, W., Zhang, X., and Li, L. (2019). Common reducing subspace model and network alternation analysis. Biometrics, 75, 11091120.
Zhang, X., Li, L., Zhou, H., Zhou, Y., and Shen, D. (2019). Tensor generalized estimating equations for longitudinal imaging analysis. Statistica Sinica, 29, 19772005.
Xia, Y. and Li, L. (2019). Matrix graph hypothesis testing and application in brain connectivity alternation detection. Statistica Sinica, 29, 303328.
Li, L., Kang, J., Lockhart, S.N., Adams, J., and Jagust, W. (2019). Spatially adaptive varying correlation analysis for multimodal neuroimaging data. IEEE Transactions on Medical Imaging, 38, 113123.
Zhu, Y. and Li, L. (2018). Multiple matrix Gaussian graphs estimation. Journal of the Royal Statistical Society, Series B., 80, 927950.
Li, Q., and Li, L. (2018). Integrative linear discriminant analysis with guaranteed error rate improvement. Biometrika, 105, 917930.
Li, X., Xu, D., Li, L., and Zhou, H. (2018). Tucker tensor regression and neuroimaging analysis. Statistics in Biosciences, 10, 520545.
Adams J.N., Lockhart, S.N., Li, L., and Jagust, W.J. (2018). Relationships between tau and glucose metabolism reflect Alzheimerâ€™s disease pathology in cognitively normal older adults. Cerebral Cortex, 29, 19972009.
Li, L. (2018). Sufficient dimension reduction. Wiley StatsRef: Statistics Reference Online, 18.
Li, L. and Zhang, X. (2017). Parsimonious tensor response regression. Journal of the American Statistical Association, 112, 11311146.
Sun, W.W. and Li, L. (2017). Sparse tensor response regression and neuroimaging analysis. Journal of Machine Learning Research, 18, 49084944.
Zhang, X. and Li, L. (2017). Tensor envelope partial least squares regression. Technometrics, 59, 426436.
Xia, Y. and Li, L. (2017). Hypothesis testing of matrix graph model with application to brain connectivity analysis. Biometrics, 73, 780791.
Li, Z., Suk, HI., Shen, D., and Li, L. (2016). Sparse multiresponse tensor regression for Alzheimer's disease study with multivariate clinical assessments. IEEE Transactions on Medical Imaging, 35, 19271936.
Kang, J. and Li, L. (2016). Discussion of “Fiber direction estimation, smoothing and tracking in diffusion MRI” by R. Wong, et al. The Annals of Applied Statistics, 10, 11621165.
2011–2015
Guo, Z., Li, L., Lu, W., and Li, B. (2015). Groupwise dimension reduction via envelope method. Journal of the American Statistical Association, 110, 15151527.
Zhou, H., and Li, L. (2014). Regularized matrix regression. Journal of the Royal Statistical Society, Series B., 76, 463483.
Ding, X., Li, L., and Zhu, L.X. (2014). Goodnessoffit testingbased selection for largepsmalln problems: a twostage ranking approach. Journal of Statistical Planning and Inference, 145, 148164.
Zhao, J., Leng, C., Li, L., and Wang, H. (2013). High dimensional influence measure. The Annals of Statistics, 41, 26392667.
Zhou, H., Li, L., and Zhu, H. (2013). Tensor regression with applications in neuroimaging data analysis. Journal of the American Statistical Association, 108, 540552.
Zhu, H., Li, L., and Zhou, H. (2012). Nonlinear dimension reduction with WrightFisher kernel for genotype aggregation and association mapping. Bioinformatics, 28, 375381.
Sun, W., and Li, L. (2012). Multiple loci mapping via modelfree variable selection. Biometrics, 68, 1822.
Li, B., Artemiou, A., and Li, L. (2011). Principal support vector machines for linear and nonlinear sufficient dimension reduction. The Annals of Statistics, 39, 31823210.
Zhu, L.P., Li, L., Li, R., and Zhu, L.X. (2011). Modelfree feature screening for ultrahigh dimensional data. Journal of the American Statistical Association, 106, 14641475.
Reich, B.J., Bondell, H.D., and Li, L. (2011). Sufficient dimension reduction via Bayesian mixture modeling. Biometrics, 67, 886895.
Lu, W., and Li, L. (2011). Sufficient dimension reduction for censored regressions. Biometrics, 67, 513523.
Zhu, H., and Li, L. (2011). Biological pathway selection through nonlinear dimension reduction. Biostatistics, 12, 429444.
Wu, Y., and Li, L. (2011). Asymptotic properties of sufficient dimension reduction with a diverging number of predictors. Statistica Sinica, 21, 707730.
Li, L., Zhu, L.P., and Zhu, L.X. (2011). Inference on the primary parameter of interest with the aid of dimension reduction estimation. Journal of the Royal Statistical Society, Series B., 73, 5980.
Shao, X., and Li, L. (2011). Datadriven multitouch attribution models. Proceedings of the 17th ACM SIGKDD international conference on knowledge discovery and data mining, San Diego, CA.
2006–2010
Li, L., Li, B., and Zhu, L.X. (2010). Groupwise dimension reduction. Journal of the American Statistical Association, 105, 11881201.
Li, L.. (2010). Dimension reduction for high dimensional data. Book chapter in Statistical Methods in Molecular Biology, Ed. Bang, H., Zhou, X., Van Epps, H.L. and Mazumdar, M. Humana Press.
Cai, Y., Chow, M.Y., Lu, W., and Li, L. (2010). Statistical feature selection from massive data in distribution fault diagnosis. IEEE Transactions on Power Systems, 25, 642648.
Cai, Y., Chow, M.Y., Lu, W., and Li, L. (2010). Evaluation of distribution fault diagnosis algorithms using ROC curves. Proceedings of Power and Energy Society General Meeting, Minneapolis, MN.
Cook, R.D., and Li, L. (2009). Dimension reduction in regressions with exponential family predictors. Journal of Computational and Graphical Statistics, 18, 774791.
Setodji, C.M., and Li, L. (2009). Model free multivariate reducedrank regression with categorical predictors. Statistica Sinica, 19, 11191136.
Li, L., and Yin, X. (2009). Longitudinal data analysis using sufficient dimension reduction method. Computational Statistics and Data Analysis, 53, 41064115.
Li, L. (2009). Exploiting predictor domain information in sufficient dimension reduction. Computational Statistics and Data Analysis, 53, 26652672.
Bondell, H.D., and Li, L. (2009). Shrinkage inverse regression estimation for model free variable selection. Journal of the Royal Statistical Society, Series B., 71, 287299.
Cornish, K.M., Kogan, C.S., Li, L., Turk, J., Jacquemont, S., and Hagerman, R.J. (2009). Lifespan changes in working memory in fragile X premutation males. Brain and Cognition, 69, 551558.
Lu, W., and Li, L. (2008). Boosting methods for nonlinear transformation models with censored survival data. Biostatistics, 9, 658677.
Li, L., and Tsai, C.L. (2008). Constrained regression model selection. Journal of Statistical Planning and Inference, 138, 39393949.
Li, L., and Yin, X. (2008). Rejoinder to “A note on sliced inverse regression with regularizations”. Biometrics, 64, 984986.
Li, L., and Lu,W. (2008). Sufficient dimension reduction with missing predictors. Journal of the American Statistical Association, 103, 822831.
Li, L. (2008). Comments on “Augmenting the bootstrap to analyze high dimensional genomic data” by S. Tyekucheva and F. Chiaromonte. Test, 17, 2224.
Li, L., and Yin, X. (2008). Sliced inverse regression with regularizations. Biometrics, 64, 124131.
Leehey, M.A., BerryKravis, E., Goetz, C.G., Zhang, L., Hall, D.A., Li, L., Rice, C.D., Lara, R., Cogswell, J., Reynolds, A., Gane, L., Jacquemont, S., Tassone, F., Grigsby, J., Hagerman, R.J., and Hagerman, P.J. (2008). FMR1 CGG repeat length predicts motor dysfunction in premutation carriers. Neurology, 70, 13971402.
Cornish, K.M., Li, L., Kogan, C.S., Jacquemont, S., Turk, J., Dalton, A., Hagerman, R.J., and Hagerman, P.J. (2008). Agedependent cognitive changes in carriers of the Fragile X Syndrome. Cortex, 44, 628636.
Li, L. (2007). Sparse sufficient dimension reduction. Biometrika, 94, 603613.
Li, L., Cook, R.D., and Tsai, C.L. (2007). Partial inverse regression method. Biometrika, 94, 615625.
Li, L., and Nachtsheim, C.J. (2007). Comment on “Fisher lecture: dimension reduction in regression” by R.D. Cook. Statistical Science, 22, 3639.
Li, L., Simonoff, J.S., and Tsai, C.L. (2007). Tobit model estimation and sliced inverse regression. Statistical Modelling, 7, 107123.
Tassone, F., Beilina, A., Carosi, C., Albertosi, S., Bagni, C., Li, L., Glover, K., Bentley, D., and Hagerman, P.J. (2007). Elevated FMR1 mRNA in premutation carriers is due to increased transcription. RNA, 13, 555562.
Tassone, F., Adams, J., BerryKravis, E.M., Cohen, S.S., Brusco, A., Leehey, M.A., Li, L., Hagerman, R.J., and Hagerman, P.J. (2007). CGG correlates with age of onset of motor signs of the Fragile Xassociated TremorAtaxia Syndrome (FXTAS). American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics/, 144, 566569.
BerryKravis, E., Goetz, C., Leehey, M.A., Hagerman, R.J., Zhang, L., Li, L., Nguyen, D., Hall, D.A., Tartaglia, N., Cogswell, J., Tassone, F., and Hagerman, P.J. (2007). Neuropathic features in fragile X premutation carriers. American Journal of Medical Genetics, Part A., 143, 1926.
Li, L., and Nachtsheim, C.J. (2006). Sparse sliced inverse regression. Technometrics, 48, 503510.
Azari, R., Li, L., and Tsai, C.L. (2006). Longitudinal data model selection. Computational Statistics and Data Analysis, 50, 30533066.
Li, L. (2006). Survival prediction of diffuse largeBcell lymphoma based on both clinical and gene expression information. Bioinformatics, 22, 466471.
2005 and earlier
Li, L., Cook, R.D., and Nachtsheim, C.J. (2005). Modelfree variable selection. Journal of the Royal Statistical Society, Series B., 67, 285299.
Li, L., and Li, W. (2005). Tabu search and perturbation methods in the construction of supersaturated designs. American Journal of Mathematical and Management Sciences, 25, 189205.
Li, L., Cook, R.D., and Nachtsheim, C.J. (2004). Clusterbased estimation for sufficient dimension reduction. Computational Statistics and Data Analysis, 47, 175193.
Li, L., and Li, H. (2004). Dimension reduction methods for microarrays with application to censored survival data. Bioinformatics, 20, 34063412.
Li, L., and Nachtsheim, C.J. (2004). Discussion of “A goodnessoffit test for singleindex models” by Y. Xia, et al. Statistica Sinica, 14, 2834.
Cook, R.D., and Li, L. (2003). Discussion of “The focused information criterion” by G. Claeskens and N.L. Hjort. Journal of the American Statistical Association, 98, 925928.
Li, L. (2002). Comment on “An adaptive estimation of dimension reduction space” by Y. Xia, et al. Journal of the Royal Statistical Society, Series B., 64, 399400.
