Lexin Li

Zhang, X., Li, L., Zhou, H., Zhou, Y., & Shen, D. (2019). TENSOR GENERALIZED ESTIMATING EQUATIONS FOR LONGITUDINAL IMAGING ANALYSIS. STATISTICA SINICA, 29(4), 1977–2005. https://doi.org/10.5705/ss.202017.0153

Guo, Z., Lu, W., & Li, L. (2015). Forward Stagewise Shrinkage and Addition for High Dimensional Censored Regression. STATISTICS IN BIOSCIENCES, 7(2), 225–244. https://doi.org/10.1007/s12561-014-9114-4

Ding, X., Li, L., & Zhu, L. (2014). Goodness-of-fit testing-based selection for large-p-small-n problems: A two-stage ranking approach. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 145, 148–164. https://doi.org/10.1016/j.jspi.2013.08.012

Zhao, J., Leng, C., Li, L., & Wang, H. (2013). HIGH-DIMENSIONAL INFLUENCE MEASURE. ANNALS OF STATISTICS, 41(5), 2639–2667. https://doi.org/10.1214/13-aos1165

Zhou, H., & Li, L. (2014). Regularized matrix regression. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 76(2), 463–483. https://doi.org/10.1111/rssb.12031

Zhou, H., Li, L., & Zhu, H. (2013). Tensor Regression with Applications in Neuroimaging Data Analysis. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 108(502), 540–552. https://doi.org/10.1080/01621459.2013.776499

Zhu, H., Li, L., & Zhou, H. (2012, September 15). Nonlinear dimension reduction with Wright-Fisher kernel for genotype aggregation and association mapping. BIOINFORMATICS, Vol. 28, pp. I375–I381. https://doi.org/10.1093/bioinformatics/bts406

Wu, Y. C., & Li, L. X. (2011). Asymptotic properties of sufficient dimension reduction with a diverging number of predictors. Statistica Sinica, 21(2), 707–730.

Zhu, H., & Li, L. (2011). Biological pathway selection through nonlinear dimension reduction. BIOSTATISTICS, 12(3), 429–444. https://doi.org/10.1093/biostatistics/kxq081

Li, L. X., Zhu, L. P., & 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, Statistical Methodology, 73, 59–80.

Zhu, L.-P., Li, L., Li, R., & Zhu, L.-X. (2011). Model-Free Feature Screening for Ultrahigh-Dimensional Data. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 106(496), 1464–1475. https://doi.org/10.1198/jasa.2011.tm10563

Sun, W., & Li, L. (2012). Multiple Loci Mapping via Model-free Variable Selection. BIOMETRICS, 68(1), 12–22. https://doi.org/10.1111/j.1541-0420.2011.01650.x

Cai, Y. X., Chow, M. Y., Lu, W. B., & Li, L. X. (2010). Evaluation of distribution fault diagnosis algorithms using ROC curves. Ieee power and energy soceity general meeting 2010. https://doi.org/10.1109/pes.2010.5588154

Li, L., Li, B., & Zhu, L.-X. (2010). Groupwise Dimension Reduction. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 105(491), 1188–1201. https://doi.org/10.1198/jasa.2010.tm09643

Lu, W., & Li, L. (2011). Sufficient Dimension Reduction for Censored Regressions. BIOMETRICS, 67(2), 513–523. https://doi.org/10.1111/j.1541-0420.2010.01490.x

Reich, B. J., Bondell, H. D., & Li, L. (2011). Sufficient Dimension Reduction via Bayesian Mixture Modeling. BIOMETRICS, 67(3), 886–895. https://doi.org/10.1111/j.1541-0420.2010.01501.x

Cook, R. D., & Li, L. (2009). Dimension Reduction in Regressions With Exponential Family Predictors. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 18(3), 774–791. https://doi.org/10.1198/jcgs.2009.08005

Li, L. (2009). Exploiting predictor domain information in sufficient dimension reduction. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 53(7), 2665–2672. https://doi.org/10.1016/j.csda.2009.01.007

Li, L., & Yin, X. (2009). Longitudinal data analysis using sufficient dimension reduction method. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 53(12), 4106–4115. https://doi.org/10.1016/j.csda.2009.04.018

Setodji, C. M., & Li, L. X. (2009). Model free multivariate reduced-rank regression with categorical predictors. Statistica Sinica, 19(3), 1119–1136.

Li, L. X., & Yin, X. R. (2008). A note on sliced inverse regression with regularizations - Reply.

Li, L. X. (2008). Augmenting the bootstrap to analyze high dimensional genomic data - Discussion. TEST, 17(1), 22–24.

Lu, W., & Li, L. (2008). Boosting method for nonlinear transformation models with censored survival data. BIOSTATISTICS, 9(4), 658–667. https://doi.org/10.1093/biostatistics/kxn005

Li, L., & Tsai, C.-L. (2008). Constrained regression model selection. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 138(12), 3939–3949. https://doi.org/10.1016/j.jspi.2008.02.006

Cornish, K. M., Kogan, C. S., Li, L., Turk, J., Jacquemont, S., & Hagerman, R. J. (2009). Lifespan changes in working memory in fragile X premutation males. BRAIN AND COGNITION, 69(3), 551–558. https://doi.org/10.1016/j.bandc.2008.11.006

Bondell, H. D., & Li, L. (2009). Shrinkage inverse regression estimation for model-free variable selection. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 71, 287–299. https://doi.org/10.1111/j.1467-9868.2008.00686.x

Li, L., & Lu, W. (2008). Sufficient dimension reduction with missing predictors. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 103(482), 822–831. https://doi.org/10.1198/016214508000000283

Cornish, K. M., Li, L., Kogan, C. S., Jacquemont, S., Turk, J., Dalton, A., … Hagerman, P. J. (2008). Age-dependent cognitive changes in carriers of the fragile X syndrome. CORTEX, 44(6), 628–636. https://doi.org/10.1016/j.cortex.2006.11.002

Tassone, F., Adams, J., Berry-Kravis, E. M., Cohen, S. S., Brusco, A., Leehey, M. A., … Hagerman, P. J. (2007). CGG repeat length correlates with age of onset of motor signs of the fragile X-associated tremor/ataxia syndrome (FXTAS). AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS, 144B(4), 566–569. https://doi.org/10.1002/ajmg.b.30482

Li, L., & Nachtsheim, C. J. (2007, February). Comment: Fisher lecture: Dimension reduction in regression. STATISTICAL SCIENCE, Vol. 22, pp. 36–39. https://doi.org/10.1214/088342307000000050

Li, L., Cook, D., & Tsai, C.-L. (2007). Partial inverse regression. BIOMETRIKA, 94(3), 615–625. https://doi.org/10.1093/biomet/asm043

Li, L., & Yin, X. (2008). Sliced inverse regression with regularizations. BIOMETRICS, 64(1), 124–131. https://doi.org/10.1111/j.1541-0420.2007.00836.x

Li, L. (2007). Sparse sufficient dimension reduction. BIOMETRIKA, 94(3), 603–613. https://doi.org/10.1093/biomet/asm044

Li, L., Simonoff, J. S., & Tsai, C.-L. (2007). Tobit model estimation and sliced inverse regression. STATISTICAL MODELLING, 7(2), 107–123. https://doi.org/10.1177/1471082X0700700201

Berry-Kravis, E., Goetz, C. G., Leehey, M. A., Hagerman, R. J., Zhang, L., Li, L., … Hagerman, P. J. (2007). Neuropathic features in fragile X premutation carriers. AMERICAN JOURNAL OF MEDICAL GENETICS PART A, 143A(1), 19–26. https://doi.org/10.1002/ajmg.a.31559

Li, L., & Nachtsheim, C. J. (2006). Sparse sliced inverse regression. TECHNOMETRICS, 48(4), 503–510. https://doi.org/10.1198/004017006000000129

Li, L. X. (2006). Survival prediction of diffuse large-B-cell lymphoma based on both clinical and gene expression information. BIOINFORMATICS, 22(4), 466–471. https://doi.org/10.1093/bioinformatics/bti824