Duong, D., Ahmad, W.U., Eskin, E., Chang, K.-W., and Li, J.J. (2018). Word and sentence embedding tools to measure semantic similarity of Gene Ontology terms by their definitions. Journal of Computational Biology in press.

Liu, H., Xu, X., and Li, J.J. (2018). A bootstrap lasso + partial ridge method to construct confidence intervals for parameters in high-dimensional sparse linear models. Statistica Sinica in press.

Li, W.V. and Li, J.J. (2018). Modeling and analysis of RNA-seq data: a review from a statistical perspective. Quantitative Biology 6(3):195-209.

Burke, J.E., Longhurst, A.D., Merkurjev, D., Sales-Lee, J., Rao, B., Moresco, J.J., Yates III, J.R., Li, J.J., and Madhani, H.D. (2018). Spliceosome profiling visualizes operations of a dynamic RNP at nucleotide resolution. Cell 173(4):1014–1030.e17.

Li, W.V. and Li, J.J. (2018). An accurate and robust imputation method scImpute for single-cell RNA-seq data. Nature Communications 9:997.

Tong, X.*, Feng, Y.*, and Li, J.J. (2018). Neyman-Pearson (NP) classification algorithms and NP receiver operating characteristics (NP-ROC). Science Advances 4(2):eaao1659.

Zhang, Y., Harris, C.J., Liu, Q., Liu, W., Ausin, I., Long, Y., Xiao, L., Feng, L., Chen, X., Xie, Y., Chen, X., Zhan, L., Feng, S., Li, J.J., Wang, H., Zhai, J., and Jacobsen. S.E. (2018). Large-scale comparative epigenomics reveals hierarchical regulation of non-CG methylation in Arabidopsis. Proc Natl Acad Sci. USA 115(5):E1069-E1074.

T Ando, KC Li. (2017). A weight-relaxed model averaging approach for high-dimensional generalized linear models. The Annals of Statistics.

KC Li, Bing-Ching Ho, Sung-Liang Yu, Gee-Chen Chang, Hsuan-Yu Chen, Pan-Chyr, Yang. (2017). Method or kit for determining lung cancer development. United States Patent Application Publication.

Li, W.V.*, Zhao, A., Zhang, S., and Li, J.J.* (2017). MSIQ: joint modeling of multiple RNA-seq samples for accurate isoform quantification. Annals of Applied Statistics in press.

Li, J.J., Chew, G.-L., and Biggin, M.D. (2017). Quantitating translational control: mRNA abundance­­-dependent and independent contributions and the mRNA sequences that specify them. Nucleic Acids Research.[link]

Jonassaint, C.R., Kang, C., Abrams, D.M., Li, J.J., Mao, J., Jia, Y., Long, Q., Sanger M., Jonassaint, J.C., De Castro, L., and Shah, N. (2017). Understanding Patterns and Correlates of Daily Pain using the Sickle Cell Disease Mobile Application to Record Symptoms via Technology (SMART). British Journal of Haematology in press.

Clifton, S.M., Kang, C., Li, J.J., Long, Q., Shah, N., and Abrams, D.M. (2017). Hybrid Statistical and Mechanistic Mathematical Model Guides Mobile Health Intervention for Chronic Pain. Journal of Computational Biology 24(7):675-688. [link]

Gao, R. and Li, J.J. (2017). Correspondence of D. melanogaster and C. elegans developmental stages revealed by alternative splicing characteristics of conserved exons. BMC Genomics 18:234. [link]

Yang, Y.*, Yang, Y.T.*, Yuan, J., Lu, Z.J. and Li, J.J. (2017). Large-scale mapping of mammalian transcriptomes identifies conserved genes associated with different cell states. Nucleic Acids Research 45(4):1657-1672.[link]

Li, W.V., Chen, Y. and Li, J.J. (2017). TROM: A Testing-Based Method for Finding Transcriptomic Similarity of Biological Samples. Statistics in Biosciences 9(1):105-136.[link]

Aragam, B., Gu, J., and Zhou, Q. (2017). Learning large-scale Bayesian networks with the sparsebn package. arXiv: 1703.04025.[link]

Aragam, B., Amini, A.A., and Zhou, Q. (2017). Learning directed acyclic graphs with penalized neighbourhood regression. arXiv: 1511.08963.[link]

Gu, J., Fu, F., and Zhou, Q. (2017). Penalized estimation of directed acyclic graphs from discrete data. arXiv: 1403.2310.[link]

Zhou, Q. and Min, S. (2017). Estimator augmentation with applications in high-dimensional group inference. Electronic Journal of Statistics, 11: 3039-3080.[link]

Zhou, Q. and Min, S. (2017). Uncertainty quantification under group sparsity. Biometrika, 104: 613-632.[link]

Kok, J.F., Ridley, D.A., Zhou, Q., Miller, R.L., Zhao, C., Heald, C.L., Ward, D.S., Albani, S., and Haustein, K. (2017). Smaller desert dust cooling effect estimated from analysis of dust size and abundance. Nature Geoscience, 10: 274-278.[link]

Li, J.J. and Tong, X. (2016). Genomic applications of the Neyman–Pearson classification paradigm. Big Data Analytics in Genomics. Springer (New York).[link]

Ye, Y. and Li, J.J. (2016). NMFP: a non-negative matrix factorization based preselection method to increase accuracy of identifying mRNA isoforms from RNA-seq data. BMC Genomics 17(Supp 1):11.[link]

Li, W.V., Razaee, Z.S. and Li, J.J. (2016). Epigenome overlap measure (EPOM) for comparing tissue/cell types based on chromatin states. BMC Genomics 17(Supp 1):10.[link]

Marchetti, Y. and Zhou, Q. (2016). Iterative subsampling in solution path clustering of noisy big data. Statistics and Its Interface, 9: 415-431. (Invited submission for special issue on big data.)[link]

Li, J.J., Huang, H., Qian, M., and Zhang, X. (2015). Chapter 24: Transcriptome analysis using next-generation sequencing. Advanced Medical Statistics (2nd Edition).[link]

Liu, Z., Dai, S., Bones, J., Ray, S., Cha, S., Karger, B. L., Li, J.J., Wilson, L., Hinckle, G., and Rossomando, A. (2015). A quantitative proteomic analysis of cellular responses to high glucose media in Chinese hamster ovary cells. Biotechnology Progress 31(4):1026-38.[link]

Li, J.J. and Biggin, M.D. (2015). Statistics requantitates the central dogma. Science 347(6226):1066-1067.[link]

Gerstein, M.B.*, Rozowsky, J.*, Yan, K.K.*, Wang, D.*, Cheng, C.*, Brown, J.B.*, Davis, C.A.*, Hillier, L*, Sisu, C.*, Li, J.J.*, Pei, B.*, Harmanci, A.O.*, Duff, M.O.*, Djebali, S.*, and 82 other authors from the modENCODE consortium (2014). Comparative analysis of the transcriptome across distant species. Nature 512(7515):445-448.[link]

Boyle, A., Araya, C., Brdlik, C., Cayting, P., Cheng, C., Cheng, Y., Gardner, K., Hillier, L., Janette, J., Jiang, L., Kasper, D., Kawli, T., Kheradpour, P., Kundaje, A., Li, J.J., and 25 other authors from the modENCODE and ENCODE consortia (2014). Comparative analysis of regulatory information and circuits across distant species. Nature 512(7515):453-456.[link]

Li, J.J., Huang, H., Bickel, P.B., and Brenner, S.E. (2014). Comparison of D. melanogaster and C. elegans developmental stages, tissues, and cells by modENCODE RNA-seq data. Genome Research 24(7):1086-1101.
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Li, J.J., Bickel, P.B., and Biggin, M.D. (2014). System wide analyses have underestimated protein abundances and transcriptional importance in animals. PeerJ 2:e270.[link]

Aragam, B. and Zhou, Q. (2015). Concave penalized estimation of sparse Gaussian Bayesian networks. Journal of Machine Learning Research, 16: 2273-2328.[link]

Shen, S., Park, J.W., Lu, Z., Lin, L., Henry, M.D., Wu, Y.N., Zhou, Q., and Xing, Y. (2014). rMATS: Robust and flexible detection of differential alternative splicing from replicate RNA-Seq data. Proceedings of the National Academy of Sciences of USA, 111: E5593-E5601.[link]

Zhou, Q. (2014). Monte Carlo simulation for Lasso-type problems by estimator augmentation. Journal of the American Statistical Association, 109: 1495-1516.[link]

Marchetti, Y. and Zhou, Q. (2014). Solution path clustering with adaptive concave penalty. Electronic Journal of Statistics, 8: 1569-1603.[link]

Cha, M. and Zhou, Q. (2014). Detecting clustering and ordering binding patterns among transcription factors via point process models. Bioinformatics, 30: 2263-2271.[link]

Levinson, M. and Zhou, Q. (2014). A penalized Bayesian approach to predicting sparse protein-DNA binding landscapes. Bioinformatics, 30: 636-643.[link]

Zhao, K., Lu, Z., Park, J.W., Zhou, Q., and Xing, Y. (2013). GLiMMPS: Robust statistical model for regulatory variation of alternative splicing using RNA-Seq data. Genome Biology, 14: R74.[link]

Lee, Y. and Zhou, Q. (2013). Co-regulation in embryonic stem cells via context-dependent binding of transcription factors. Bioinformatics, 29: 2162-2168.[link]

Fu, F. and Zhou, Q. (2013). Learning sparse causal Gaussian networks with experimental intervention: Regularization and coordinate descent. Journal of the American Statistical Association, 108: 288-300.[link]

Fisher, W.W., Li, J.J., Hammonds, A.S., Brown, J.B., Pfeiffer, B., Weiszmann, R., MacArthur, S., Thomas, S., Stamatoyannopoulos, J.A., Eisen, M.B., Bickel, P.B., Biggin, M.D., and Celniker, S.E. (2012). DNA regions bound at low occupancy by transcription factors do not drive patterned reporter gene expression in Drosophila. Proc Natl Acad Sci. USA 109(52):21330–21335.[link]

The ENCODE Project Consortium (2012). An integrated encyclopedia of DNA elements in the human genome. Nature 489(7414):57–74.[link]

Gao, Q., Ho, C., Jia, Y., Li, J.J., and Huang, H. (2012). Biclustering of linear patterns in gene expression data (CLiP). Journal of Computational Biology 19(6):619-631.[link]

Li, J., Li, J., and Chen, B. (2012). Oct4 was a novel target of Wnt signaling pathway. Molecular and Cellular Biochemistry 362:233–240.[link]

Tang, W. and Zhou, Q. (2012). Finding multiple minimum-energy conformations of the hydrophobic-polar protein model via multidomain sampling. Physical Review E, 86: 031909.[link]

Shen, S., Park, J.W., Huang, J., Dittmar, K.A., Lu, Z., Zhou, Q., Carstens, R.P., and Xing, Y. (2012). MATS: A Bayesian framework for flexible detection of differential alternative splicing from RNA-Seq data. Nucleic Acids Research, 40: e61.[link]

Li, J.J., Jiang, C.-R., Brown, B.J., Huang, H., and Bickel, P.J. (2011). Sparse linear modeling of RNA-seq data for isoform discovery and abundance estimation. Proc Natl Acad Sci. USA 108(50):19867-19872.
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Zhou, Q. (2011). Multi-domain sampling with applications to structural inference of Bayesian networks. Journal of the American Statistical Association, 106: 1317-1330.[link]

Chen, G. and Zhou, Q. (2011). Searching ChIP-Seq genomic islands for combinatorial regulatory codes in mouse embryonic stem cells. BMC Genomics, 12: 515.[link]

Zhou, Q. (2011). Random walk over basins of attraction to construct Ising energy landscapes. Physical Review Letters, 106: 180602. [link]

Zhou, Q. (2010). On weight matrix and free energy models for sequence motif detection. Journal of Computational Biology, 17: 1621-1638.[link]

Mason, M.J., Plath, K., and Zhou, Q. (2010). Identification of context-dependent motifs by contrasting ChIP binding data. Bioinformatics, 26: 2826-2832.[link]

Chen, G. and Zhou, Q. (2010). Heterogeneity in DNA multiple alignments: Modeling, inference, and applications in motif finding. Biometrics, 66: 694-704.[link]

Zhou, Q. (2010). Review of “A Guide to QTL Mapping with R/qtl” by Broman and Sen. Journal of Statistical Software, 32: Book Review 5.
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MacArthur, S.*, Li, X.Y.*, Li, J.*, Brown, J.B., Chu, H.C., Zeng, L., Grondona, B.P., Hechmer, A., Simirenko, L., Keranen, S.V., Knowles, D.W., Stapleton, M., Bickel, P., Biggin, M.D., and Eisen, M.B. (2009). Developmental roles of 21 Drosophila transcription factors are determined by quantitative differences in binding to an overlapping set of thousands of genomic regions. Genome Biology 10:R80.[link]

Zhou, Q. and Gupta, M. (2009). Regulatory motif discovery: From decoding to meta-analysis. New Developments in Biostatistics and Bioinformatics, chp 8: 179-208, World Scientific.[link]

Ouyang, Z., Zhou, Q., and Wong, W.H. (2009). ChIP-Seq of transcription factors predicts absolute and differential gene expression in embryonic stem cells. Proceedings of the National Academy of Sciences of USA, 106: 21521-21526.[link]

Mason, M.J., Fan, G., Plath, K., Zhou, Q., and Horvath, S. (2009). Signed weighted gene co-expression network analysis of transcriptional regulation in murine embryonic stem cells. BMC Genomics, 10: 327.
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Gao, K., Zhou, H., Zhang, L., Lee, J.W., Zhou, Q., Hu, S., Wolinsky, L.E., Farrell, J., Eibl, G., and Wong, D.T. (2009). Systemic disease-induced salivary biomarker profiles in mouse models of melanoma and non-small cell lung cancer. PLoS One, 4: e5875.[link]

Zhou, Q. and Wong, W.H. (2009). Energy landscape of a spin-glass model: Exploration and characterization. Physical Review E, 79: 051117.
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Sridharan, R.*, Tchieu, J.*, Mason, M.J.*, Yachechko, R., Kuoy, E., Horvath, S., Zhou, Q., and Plath, K. (2009). Role of the murine reprogramming factors in the induction of pluripotency. Cell, 136: 364-377. (*Equally contributed authors.)[link]

Zhou, Q. and Wong, W.H. (2008). Reconstructing the energy landscape of a distribution from Monte Carlo samples. Annals of Applied Statistics, 2: 1307-1331.[link]

Zhou, Q. and Liu, J.S. (2008). Extracting sequence features to predict protein-DNA interactions: A comparative study. Nucleic Acids Research, 36: 4137-4148.[link]

Sung-Liang Yu,Hsuan-Yu Chen, Gee-Chen Chang,Chih-Yi Chen,Huei-Wen Chen, Sher Singh,Chiou-Ling Cheng, Chong-Jen Yu, Yung-Chie Lee, Han-Shiang Chen,Te-Jen Su, Ching-Cheng Chiang,Han-Ni Li,Qi-Sheng Hong, Hsin-Yuan Su, Chun-Chieh Chen,Wan-Jiun Chen, Chun-Chi Liu,Wing-Kai Chan,Wei J. Chen, Ker-Chau Li,Jeremy J.W. Chen, and Pan-Chyr Yang (2008) MicroRNA Signature Predicts Survival and Relapse in Lung Cancer. Cancer Cell 13, 4857.[link]

Liu J.S. and Zhou, Q. (2007). Predictive modeling approaches for studying protein-DNA binding. Proceedings of the Fourth International Congress of Chinese Mathematicians, Vol. 4: 151-167, Higher Education Press and International Press.[link]

Zhou, Q., Chipperfield, H., Melton, D.A., and Wong, W.H. (2007). A gene regulatory network in mouse embryonic stem cells. Proceedings of the National Academy of Sciences of USA, 104: 16438-16443.[link]

Zhou, Q. and Wong, W.H. (2007). Coupling hidden Markov models for the discovery of cis-regulatory modules in multiple species. Annals of Applied Statistics, 1: 36-65.[link]

Li, KC, Palotie A, Yuan, S, Bronnikov, D., Chen D., Wei X., Choi, O., Saarela J., Peltonen L. (2007) Finding disease candidate genes by liquid association. Genome Biology, 8, R205. oi:10.1186/gb-2007-8-10-r205.
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Yuan, S., and Li. K.C. (2007) Context-dependent Clustering for Dynamic Cellular State Modeling of Microarray Gene Expression. Bioinformatics 2007; 15;23(22):3039-47.[link]

Wei Sun; Tianwei Yu; Ker-Chau Li (2007). Detection of eQTL modules mediated by activity levels of transcription factors. Bioinformatics; 2007 Sep 1;23(17):2290-7.[link]

Chun-Chi Liu, Chin-Chung Lin, Ker-Chau Li, Wen-Shyen E. Chen, Jiun-Ching Chen, Ming-Te Yang, Pan-Chyr Yang, Pei-Chun Chang, and Jeremy J.W. Chen. (2007) Genome-wide identification of the specific oligonucleotides using artificial neural network and computational genomic analysis. BMC Bioinformatics. 8:164.[link]

Tianwei Yu, Hui Ye, Wei Sun, Ker-Chau Li, Zugen Chen, Sharoni Jacobs, Dione K Bailey, David T Wong and Xiaofeng Zhou (2007). A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array. BMC Bioinformatics, 8:145.[link]

Kou, S.C.*, Zhou, Q.*, and Wong, W.H. (2006). Equi-energy sampler with applications in statistical inference and statistical mechanics (with discussion). Annals of Statistics, 34: 1581-1652. (*Equally contributed authors.)[link]

Johnson, D.S., Zhou, Q., Yagi, K., Satoh, N., Wong, W.H., and Sidow, A. (2005). De novo discovery of a tissue-specific gene regulatory module in a chordate. Genome Research, 15: 1315-1324.
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Hong, P., Liu, X.S., Zhou, Q., Lu, X., Liu, J.S., and Wong, W.H. (2005). A boosting approach for motif modeling using ChIP-chip data. Bioinformatics, 21: 2636-2643.[link]

Yu, T., and Li, K.C. (2005). Inference of transcriptional regulatory network by two-stage constrained space factor analysis. Bioinformatics 21, 4033-4038.[link]

Yu, T., Sun, W., Yuan , S., and Li, K.C. (2005). Study of coordinative gene expression at the biological process level. Bioinformatics 21 3651-3657.
Li, K.C.o, Ching-Ti Liu, Wei Sun, Shinsheng Yuan and Tianwei Yu (2004). A system for enhancing genome-wide co-expression dynamics study. Proceedings of National Academy of Sciences 101 , 15561-15566.[link]

Xie, J., Li, K.C., and Bina, M. (2004) A Bayesian Insertion/Deletion Algorithm for Distant Protein Motif Searching via Entropy Filtering. J. American Statistical Association , 99, 409-420.[link]

Li, K.C., and Yuan, S. (2004) A functional genomic study on NCI’s anticancer drug screen. The Pharmacogenomics Journal, 4, 127-135.
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Zhou, Q. and Wong, W.H. (2004). CisModule: De novo discovery of cis-regulatory modules by hierarchical mixture modeling. Proceedings of the National Academy of Sciences of USA, 101: 12114-12119.[link]

Zhou, Q. and Liu, J.S. (2004). Modeling within-motif dependence for transcription factor binding site predictions. Bioinformatics, 20: 909-916.[link]

Jensen, S.T., Liu, X.S., Zhou, Q., and Liu, J.S. (2004). Computational discovery of gene regulatory binding motifs: A Bayesian perspective. Statistical Science, 19: 188-204.[link]

Zhou, Q. and Li, Y.D. (2003). Directed variation in evolution strategies. IEEE Transactions on Evolutionary Computation, 7: 356-366.[link]

Li, K.C., Aragon, Y, Shedden, K. and Thomos-Agan C., C.(2003). Dimension reduction for multivariate response data. Journal of American Statistical Association. 98, 99-106.[link]

Li, K.C. (2002) Genome-wide co-expression dynamics: theory and application. Proceedings of National Academy of Science. 99, 16875-16880.[link]

Li, K.C., Yan, M. and Yuan, S. (2002) A simple statistical model for depicting the cdc-15 synchronized yeast cell cycle-regulated gene expression data. Statistica Sinica, 12, 141-158.[link]

Li, K.C. and Shedden. K (2002). Identification of shared common components in large ensembles of time series using dimension reduction. Journal of American Statistical Association, 97, 759-765.

Ji, H.K.*, Zhou, Q.*, Wen, F., Xia, H.Y., Lu, X., and Li, Y.D. (2001). AsMamDB: An alternative splice database of mammals. Nucleic Acids Research, 29: 260-263. (*Equally contributed authors.)[link]

Li, K.C. and Shedden, K. (2001). Monte Carlo deconvolution of digital signals guided by the inverse filter. Journal of Amer. Stat. Assoc. 96, 1014-1021.[link]

Li, K.C., Lue, H.H, and Chen, C.H. (2000) Interactive tree-structured regression via principal Hessian directions. Journal Amer. Statist. Assoc. 95, 547-560.[link]

Li, K.C., J.L. Wang, and C.H. Chen (1999). Dimension reduction for censored regression data. Ann. Stat.. 27, 1-23.[link]

Chen, C.H., and Li, K.C. (1998) Generalization of Fisher’s linear discriminant analysis via the approach of sliced inverse regression. Manuscript.[link]

Li, K.C. and Shedden, K. (1998). Monte Carlo blind deconvolution guided by the inverse filter. Manuscript.[link]

Chen, C.H. and Li, K. C. (1998). Can SIR be as popular as multiple linear regression? Statistica Sinica 8, 289-316. Comment on ”Principal Hessian Direction, revisited.” Journal of American Statistical Association. 93, 94-97.[link]

Li, K.C., and Lue, H.H (1998) Interactive tree-structured regression via principal Hessian directions. Manuscript.[link]

Li, K.C., and Chen, C. H. (1997) A Three-way subclassification approach to multiple-class discriminant analysis. Manuscript.

Li, K.C. (1997). “Sliced inverse regression” . In Encyclopedia of Statistical Sciences. Update vol 1. page 497-499. Edited by S. Kotz, C. Read, and D. Banks. John Wiley, New York.

Li, K. C. (1997). Nonlinear confounding in high dimensional regression. Ann. Statist. 25, 577-612.[link]

Filliben, J. and Li, K. C. (1997). A systematic approach to the analysis of complex interaction patterns in 2-level factorial designs. Technometrics 39, 286-297.

Horng, M.J., K.C. Li, and W.W. Yeh. (1996). Uncertainty analysis of groundwater modeling via statistical dimension reduction. Manuscript.

Cheng, C. S. and Li, K. C. (1995) A study of the method of principal Hessian direction for analysis of data from designed experiments, Statistica Sinica 5, 617-640.[link]

Carroll, R. and Li, K.C.(1995). Binary regressors in dimension reduction models: a new look at treatment comparisons. Statistica Sinica 5, 667-688.
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Li, K.C., Aragon, Y, and Thomos-Agan, C.(1995). Analysis of multivariate outcome data: SIR and a nonlinear theory of Hotelling’s most predictable variates. Submitted to Journal Amer. Statist. Assoc.

Hall, P. and Li, K. C. (1993). On almost linearity of low dimensional projection from high dimensional data. Ann. Stat. 21, 867-889.[link]

Lee, J. J., Li, K. C. and Elashoff, R. M. (1993). On re-censoring for censored paired data. J. Amer. Stat. Assoc. 88, 104-118.[link]

Li, K. C. (1992). On principal Hessian directions for data visualization and dimension reduction: another application of Stein’s lemma. J. Ameri. Stat. Assoc. 87, 1025-1039.[link]

Li, K. C. (1992). Uncertainty analysis for mathematical models with SIR. In ”Probability and Statistics”, 138-162, edited by Jiang Ze-Pei, Yan Shi-Jian, Cheng Ping, and Wu Rong, World Scientific, Singapore.

Carroll, R. J. and Li, K. C. (1992). Measurement error regression with unknown link: dimension reduction and data visualization. J. Amer. Stat. Assoc. 87, 1040-1050.[link]

Duan, N. and Li, K. C. (1991). A bias bound for applying linear regression to a general linear model. Statistica Sinica 1, 127-136.

Duan, N. and Li, K. C. (1991). Slicing regression: a link-free regression method. Ann. Stat. 19, 505-530.[link]

Li, K. C. (1991). Sliced inverse regression for dimension reduction, with discussions. J. Amer. Statist. Assoc. 86, 316-342.[link]

Cheng, C. S. and Li, K. C. (1990) Characterization of invariant spaces under a symmetric real matrix and its permutations. Linear Algebra and its Applications 127, pp 503-516.[link]

Li, K. C. (1990). Data-visualization with SIR : a transformation-based projection pursuit method. Technical Report.

Li, K. C. and Duan, N. (1989). Regression analysis under link violation. Ann. Statist. 17, 1009-1052.[link]

Li, K. C. and Ylvisaker, D. (1989). Another look at adaptation on the average. Statistics and Probability Letters 7, 381-383.[link]

Li, K. C. (1989). Honest confidence regions for nonparametric regression. Ann. Statist. 17, 1001-1008.[link]

Marquis, M. S., Duan, N., Li, K. C., Berry, S. H., Haaga, J.G. and Lohr, K. N. (1988) Beneficiary incentives to participate in alternative health plans: a research design. The RAND publication series.

Cheng, C. S. and Li, K. C. (1987). Optimality criteria in survey sampling. Biometrika 74, 337-345.[link]

Li, K. C. (1987). Asymptotic optimality for Cp, CL, cross-validation and generalized cross-validation: discrete index set. Ann. Statist. 15, 958-975.[link]

Duan, N. and Li, K. C. (1987). Distribution-free and link-free estimation for the sample selection model. J. Econometrics 35, 25-35.[link]

Li, K. C. (1986). Asymptotic optimality of CL and generalized cross validation in ridge regression with application to spline smoothing. Ann. Statist. 14, 1101-1112.[link]

Duan, N. and Li, K. C. (1986). The ordinary least squares estimation for the general link models with applications. International Statist. Symposium, Taipei, R.O.C. 1, 505-523.

Li, K. C. (1985). From Stein’s unbiased risk estimates to the method of generalized cross validation. Ann. Statist. 13, 1352-1377.[link]

Li, K. C. (1984). Consistency for cross-validated nearest neighbor estimates in nonparametric regression. Ann. Statist. 12, 230-240.[link]

Li, K. C. (1984). Robust regression designs when the design space consists of finitely many points. Ann. Statist. 12, 269-282.[link]

Li, K. C. (1984). Regression models with infinitely many parameters: consistency of bounded linear functionals. Ann. Statist. 12, 601-611.[link]

Li, K. C., and Hwang, J. T. (1984). The data-smoothing aspect of Stein estimates. Ann. Statist. 12, 887-897.[link]

Cheng, C. S. and Li, K. C. (1984). The strong consistency of M-estimators in linear models. J. Multivariate Analysis 15, 91-98.[link]

Li, K. C. (1983). Minimaxity for randomized designs: some general results. Ann. Statist. 11, 225-239.[link]

Cheng, C. S. and Li, K. C. (1983). A minimax approach to sample surveys. Ann.Statist. 11, 552-563.[link]

Li, K. C., and Notz, W. (1982). Robust designs for nearly linear regression. J. Stat. Planning and Inference 6, 135-151.[link]

Li, K. C. (1982). Minimaxity of the method of regularization on stochastic processes. Ann. Statist. 10, 937-942.[link]