Year |
Citation |
Score |
2022 |
Dai X, Lyu X, Li L. Kernel Knockoffs Selection for Nonparametric Additive Models. Journal of the American Statistical Association. 118: 2158-2170. PMID 38143786 DOI: 10.1080/01621459.2022.2039671 |
0.303 |
|
2022 |
Li L, Zeng J, Zhang X. Generalized Liquid Association Analysis for Multimodal Data Integration. Journal of the American Statistical Association. 118: 1984-1996. PMID 38099062 DOI: 10.1080/01621459.2021.2024437 |
0.336 |
|
2022 |
Dai X, Li L. Orthogonalized Kernel Debiased Machine Learning for Multimodal Data Analysis. Journal of the American Statistical Association. 118: 1796-1810. PMID 37771509 DOI: 10.1080/01621459.2021.2013851 |
0.348 |
|
2022 |
Zhao Y, Li L. Multimodal data integration via mediation analysis with high-dimensional exposures and mediators. Human Brain Mapping. PMID 35129252 DOI: 10.1002/hbm.25800 |
0.308 |
|
2021 |
Dai X, Li L. Kernel Ordinary Differential Equations. Journal of the American Statistical Association. 117: 1711-1725. PMID 36845295 DOI: 10.1080/01621459.2021.1882466 |
0.322 |
|
2020 |
Zhao Y, Li L, Caffo BS. Multimodal neuroimaging data integration and pathway analysis. Biometrics. PMID 32789850 DOI: 10.1111/Biom.13351 |
0.399 |
|
2019 |
Zhang X, Li L, Zhou H, Zhou Y, Shen D. TENSOR GENERALIZED ESTIMATING EQUATIONS FOR LONGITUDINAL IMAGING ANALYSIS. Statistica Sinica. 29: 1977-2005. PMID 32523321 DOI: 10.5705/Ss.202017.0153 |
0.378 |
|
2019 |
Ye Y, Xia Y, Li L. Paired test of matrix graphs and brain connectivity analysis. Biostatistics (Oxford, England). PMID 31631218 DOI: 10.1093/Biostatistics/Kxz037 |
0.306 |
|
2019 |
Wang W, Zhang X, Li L. Common Reducing Subspace Model and Network Alternation Analysis. Biometrics. PMID 31140579 DOI: 10.1111/Biom.13099 |
0.464 |
|
2018 |
Li X, Xu D, Zhou H, Li L. Tucker Tensor Regression and Neuroimaging Analysis. Statistics in Biosciences. 10: 520-545. PMID 34354773 DOI: 10.1007/s12561-018-9215-6 |
0.302 |
|
2018 |
Li Q, Li L. Integrative linear discriminant analysis with guaranteed error rate improvement. Biometrika. 105: 917-930. PMID 31762476 DOI: 10.1093/Biomet/Asy047 |
0.391 |
|
2018 |
Zhu Y, Li L. Multiple Matrix Gaussian Graphs Estimation. Journal of the Royal Statistical Society. Series B, Statistical Methodology. 80: 927-950. PMID 30505211 DOI: 10.1111/Rssb.12278 |
0.357 |
|
2018 |
Li L, Kang J, Lockhart SN, Adams J, Jagust WJ. Spatially Adaptive Varying Correlation Analysis for Multimodal Neuroimaging Data. Ieee Transactions On Medical Imaging. PMID 30028695 DOI: 10.1109/Tmi.2018.2857221 |
0.313 |
|
2018 |
Li X, Xu D, Zhou H, Li L. Tucker Tensor Regression and Neuroimaging Analysis Statistics in Biosciences. 10: 520-545. DOI: 10.1007/S12561-018-9215-6 |
0.409 |
|
2017 |
Li L, Zhang X. Parsimonious Tensor Response Regression Journal of the American Statistical Association. 112: 1131-1146. DOI: 10.1080/01621459.2016.1193022 |
0.42 |
|
2016 |
Xia Y, Li L. Hypothesis testing of matrix graph model with application to brain connectivity analysis. Biometrics. PMID 27959470 DOI: 10.1111/Biom.12633 |
0.365 |
|
2016 |
Li Z, Suk HI, Shen D, Li L. Sparse Multi-Response Tensor Regression for Alzheimer's Disease Study with Multivariate Clinical Assessments. Ieee Transactions On Medical Imaging. PMID 26960221 DOI: 10.1109/Tmi.2016.2538289 |
0.308 |
|
2016 |
Zhang X, Li L. Tensor Envelope Partial Least-Squares Regression Technometrics. 59: 426-436. DOI: 10.1080/00401706.2016.1272495 |
0.411 |
|
2015 |
Guo Z, Li L, Lu W, Li B. Groupwise Dimension Reduction via Envelope Method. Journal of the American Statistical Association. 110: 1515-1527. PMID 26973362 DOI: 10.1080/01621459.2014.970687 |
0.411 |
|
2015 |
Guo Z, Lu W, Li L. Forward Stagewise Shrinkage and Addition for High Dimensional Censored Regression. Statistics in Biosciences. 7: 225-244. PMID 26904152 DOI: 10.1007/S12561-014-9114-4 |
0.457 |
|
2014 |
Zhou H, Li L. Regularized matrix regression. Journal of the Royal Statistical Society. Series B, Statistical Methodology. 76: 463-483. PMID 24648830 DOI: 10.1111/Rssb.12031 |
0.412 |
|
2014 |
Ding X, Li L, Zhu L. 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. DOI: 10.1016/J.Jspi.2013.08.012 |
0.351 |
|
2013 |
Zhou H, Li L, Zhu H. Tensor Regression with Applications in Neuroimaging Data Analysis. Journal of the American Statistical Association. 108: 540-552. PMID 24791032 DOI: 10.1080/01621459.2013.776499 |
0.451 |
|
2013 |
Zhao J, Leng C, Li L, Wang H. High Dimensional Influence Measure Annals of Statistics. 41: 2639-2667. DOI: 10.1214/13-Aos1165 |
0.404 |
|
2012 |
Zhu H, Li L, Zhou H. Nonlinear dimension reduction with Wright-Fisher kernel for genotype aggregation and association mapping. Bioinformatics (Oxford, England). 28: i375-i381. PMID 22962455 DOI: 10.1093/Bioinformatics/Bts406 |
0.359 |
|
2012 |
Sun W, Li L. Multiple loci mapping via model-free variable selection. Biometrics. 68: 12-22. PMID 21838809 DOI: 10.1111/J.1541-0420.2011.01650.X |
0.374 |
|
2011 |
Zhu L, Li L, Li R, Zhu L. Model-Free Feature Screening for Ultrahigh Dimensional Data. Journal of the American Statistical Association. 106: 1464-1475. PMID 22754050 DOI: 10.1198/Jasa.2011.Tm10563 |
0.406 |
|
2011 |
Wu Y, Li L. ASYMPTOTIC PROPERTIES OF SUFFICIENT DIMENSION REDUCTION WITH A DIVERGING NUMBER OF PREDICTORS. Statistica Sinica. 2011: 707-730. PMID 22140299 DOI: 10.5705/Ss.2011.031A |
0.44 |
|
2011 |
Zhu H, Li L. Biological pathway selection through nonlinear dimension reduction. Biostatistics (Oxford, England). 12: 429-44. PMID 21252081 DOI: 10.1093/Biostatistics/Kxq081 |
0.388 |
|
2011 |
Reich BJ, Bondell HD, Li L. Sufficient dimension reduction via bayesian mixture modeling. Biometrics. 67: 886-95. PMID 21039398 DOI: 10.1111/J.1541-0420.2010.01501.X |
0.453 |
|
2011 |
Lu W, Li L. Sufficient dimension reduction for censored regressions. Biometrics. 67: 513-23. PMID 20880013 DOI: 10.1111/J.1541-0420.2010.01490.X |
0.475 |
|
2011 |
Li B, Artemiou A, Li L. Principal support vector machines for linear and nonlinear sufficient dimension reduction Annals of Statistics. 39: 3182-3210. DOI: 10.1214/11-Aos932 |
0.376 |
|
2011 |
Li L, Zhu L, Zhu L. 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. DOI: 10.1111/J.1467-9868.2010.00759.X |
0.431 |
|
2010 |
Li L. Dimension reduction for high-dimensional data. Methods in Molecular Biology (Clifton, N.J.). 620: 417-34. PMID 20652514 DOI: 10.1007/978-1-60761-580-4_14 |
0.409 |
|
2010 |
Li L, Li B, Zhu L. Groupwise Dimension Reduction Journal of the American Statistical Association. 105: 1188-1201. DOI: 10.1198/Jasa.2010.Tm09643 |
0.4 |
|
2010 |
Cai Y, Chow M, Lu W, Li L. Statistical Feature Selection From Massive Data in Distribution Fault Diagnosis Ieee Transactions On Power Systems. 25: 642-648. DOI: 10.1109/Tpwrs.2009.2036924 |
0.316 |
|
2009 |
Cook RD, Li L. Dimension Reduction in Regressions With Exponential Family Predictors Journal of Computational and Graphical Statistics. 18: 774-791. DOI: 10.1198/Jcgs.2009.08005 |
0.431 |
|
2009 |
Bondell HD, Li L. Shrinkage inverse regression estimation for model-free variable selection Journal of the Royal Statistical Society: Series B (Statistical Methodology). 71: 287-299. DOI: 10.1111/J.1467-9868.2008.00686.X |
0.431 |
|
2009 |
Li L, Yin X. Longitudinal data analysis using sufficient dimension reduction method Computational Statistics & Data Analysis. 53: 4106-4115. DOI: 10.1016/J.Csda.2009.04.018 |
0.442 |
|
2009 |
Li L. Exploiting predictor domain information in sufficient dimension reduction Computational Statistics & Data Analysis. 53: 2665-2672. DOI: 10.1016/J.Csda.2009.01.007 |
0.366 |
|
2008 |
Lu W, Li L. Boosting method for nonlinear transformation models with censored survival data. Biostatistics (Oxford, England). 9: 658-67. PMID 18344565 DOI: 10.1093/Biostatistics/Kxn005 |
0.419 |
|
2008 |
Li L, Yin X. Sliced inverse regression with regularizations. Biometrics. 64: 124-31. PMID 17651455 DOI: 10.1111/J.1541-0420.2007.00836.X |
0.455 |
|
2008 |
Li L, Lu W. Sufficient Dimension Reduction With Missing Predictors Journal of the American Statistical Association. 103: 822-831. DOI: 10.1198/016214508000000283 |
0.496 |
|
2008 |
Li L, Tsai CL. Constrained regression model selection Journal of Statistical Planning and Inference. 138: 3939-3949. DOI: 10.1016/J.Jspi.2008.02.006 |
0.332 |
|
2007 |
Li L, Nachtsheim CJ. Comment: Fisher lecture: Dimension reduction in regression Statistical Science. 22: 36-39. DOI: 10.1214/088342307000000050 |
0.681 |
|
2007 |
Li L, Simonoff JS, Tsai C. Tobit Model Estimation and Sliced Inverse Regression Statistical Modelling. 7: 107-123. DOI: 10.1177/1471082X0700700201 |
0.4 |
|
2007 |
Li L. Sparse sufficient dimension reduction Biometrika. 94: 603-613. DOI: 10.1093/Biomet/Asm044 |
0.465 |
|
2007 |
Li L, Cook RD, Tsai CL. Partial inverse regression Biometrika. 94: 615-625. DOI: 10.1093/Biomet/Asm043 |
0.439 |
|
2006 |
Li L. Survival prediction of diffuse large-B-cell lymphoma based on both clinical and gene expression information. Bioinformatics (Oxford, England). 22: 466-71. PMID 16339281 DOI: 10.1093/Bioinformatics/Bti824 |
0.317 |
|
2006 |
Li L, Nachtsheim CJ. Sparse sliced inverse regression Technometrics. 48: 503-510. DOI: 10.1198/004017006000000129 |
0.68 |
|
2006 |
Azari R, Li L, Tsai C. Longitudinal data model selection Computational Statistics & Data Analysis. 50: 3053-3066. DOI: 10.1016/J.Csda.2005.05.009 |
0.356 |
|
2005 |
Li L, Cook RD, Nachtsheim CJ. Model-free variable selection Journal of the Royal Statistical Society. Series B: Statistical Methodology. 67: 285-299. DOI: 10.1111/J.1467-9868.2005.00502.X |
0.676 |
|
2004 |
Li L, Cook RD, Nachtsheim CJ. Cluster-based estimation for sufficient dimension reduction Computational Statistics and Data Analysis. 47: 175-193. DOI: 10.1016/J.Csda.2003.10.017 |
0.65 |
|
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