Publications

tsingIn: Academic Achievement
2017.7-2018.6
  • Zhang, Y. and Yang, L. ,2018. A smooth simultaneous confidence band for correlation curve. TEST27(2)，247-269.
  • Zhang, R., Deng, W., Zhu, Y. ,2017. Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications. Proceedings of the 9th Asian Conference on Machine Learning (ACML17), Seoul, Korea, 2017.
  • Pan, C. and Zhu, M. ,2017. Group Additive Structure Identification for Kernel Nonparametric Regression. Advances in Neural Information Processing Systems 30 (NIPS 2017).
  • Huang, Q. and Zhu, Y. 2017. SPOT: Sparse Optimal Transformations for High Dimensional Variable Selection and Exploratory Regression Analysis. Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2017).
  • Cheng, L., Zeng, P., and Zhu, Y. (2017) BS-SIM: An Effective Variable Selection Method for High-dimensional Single Index Model. Electronic Journal of Statistics, 11(2) 3522-3548.
  • 邓柯 (2017) 统计学与人文研究的哲学思辨.《公共管理评论》, 2017年第3期（总第26期）, 24-38.
  • Sun Z. Wang T., Deng K., Wang X.F., Lafyatis R., Ding Y., Hu M., Chen W. (2018) DIMM-SC: a Dirichlet Mixture Model for Clustering Droplet-Based Single Cell Transcriptomic Data. Bioinformatics34(1), 139-146.
  • Li, D., Zhang, X.F., Zhu, K. and Ling, S. (2018) The ZD-GARCH model: A new way to study heteroscedasticity. Journal of Econometrics 202, 1-17.
  • Liu, F., Li, D.* and Kang, X.M. (2018) Sample path properties of an explosive double autoregressive model. Econometric Reviews 37, 484-490.
  • Hou, L., Sun, N., Mane, S., Sayward, F., 2017. Impact of Genotyping Errors on Statistical Power of Association Test in Genomic Analyses: A Case Study. Genetic Epidemiology , 41, pp.152-162.
  • Williams, K.R., Colangelo, C.M., Hou, L. and Chung, L., 2017. Use of a Targeted Urine Proteome Assay (TUPA) to identify protein biomarkers of delayed recovery after kidney transplant. Proteomics Clin Appl 11, pp.7-8.
  • Can,A., Castro, V.M., Ozdemir, Y.H., Dagen, D., Dligach, D., Finan, S., Yu,S., Gainer,V., Shadick, N.A., Murphy, S., Cai, T.C., Savova, G., Weiss, S.T., Du, R.*,2018. Alcohol Consumption and Aneurysmal Subarachnoid Hemorrhage. Translational Stroke Research 9(1), pp.13-19.
  • Can,A., Castro, V.M., Yu, S., Dligach, D., Finan, S., Gainer, V., Shadick, N.A., Savova, G., Murphy, S., Cai, T., Weiss, s.t. and Du, R*. 2018. Antihyperglycemic Agents are Inversely Associated with Intracranial Aneurysm Rupture. Stroke 49(1), 34-39.
  • Yu, S., Ma, Y., Gronsbell, J., Cai, T., Ananthakrishnan, A.N., Gainer, V.S., Churchill, S.E., Szolovits, P., Murphy, S.N. and Kohane, I.S., 2017. Enabling phenotypic big data with PheNorm. Journal of the American Medical Informatics Association 25(1), 54-60.
  • Can,A., Castro, V.M., Ozdemir, Y.H., Dagen, S., Yu, S., Dligach, D., Finan, S., Gainer, V., Shadick, N.A. and Murphy, S., 2017, Association of Intracranial Aneurysm Rupture with Smoking Duration, Intensity, and Cessation. Neurology 89（13），1408-1415.
  • McCoy Jr, TH., Yu, S., Hart, K.L., Castro, V.M., Brown, H.E., Rosenquist, J.N., Doyle, A.E., Vuijk, P.J., Cai, T. and Perlis, R.H., 2018. High Throughput Phenotyping for Dimensional Psychopathology in Electronic Health Records. Biological Psychiatry (2018), 83(12), 997-1004.
  • McCoy Jr, TH., Castro, V.M., Hart, K.L., Pellegrini, A.M., Yu,S., Cai, T. and Perlis, R.H.,2018. Genome-wide Association Study of Dimensional Psychopathology Using Electronic Health Records. Biological Psychiatry, 83(12), 1005-1011.
  • Liu, H., and Yu,B., 2017. Comments on: High dimensional simultaneous inference with the bootstrap. Test 26(4), 740-750.
  • Lin, Q., Zhao, Z., and Liu, J., 2018. On consistency and sparsity of sliced inverse regression in high dimensions. Annals of Statistics 46(2), 580-610.

 

2016.8-2017.7
  • Shao, Q. and Yang, L. (2017) Oracally efficient estimation and consistent model selection for auto-regressive moving average time series with trend. Journal of the Royal Statistical Society Series B 79(2), 507-524.
  • Zheng, S., Liu, R., Yang, L. and Härdle, W. (2016) Statistical inference for generalized additive models: simultaneous confidence corridors and variable selection. TEST 25(4), 607-626.
  • Wang, J., Wang, S., and Yang, L. (2016) Simultaneous confidence bands for the distribution function of a finite population and its superpopulation. TEST25(4), 692-709.
  • Li, D. and Tong, H. (2016) Nested sub-sample search algorithm for estimation of threshold models. Statistica Sinica 26(4), 1543-1554.
  • Hou L., Sun N., Mane S., et al. (2016) Impact of genotyping errors on statistical power of association tests in genomic analyses: A case study. Genetic Epidemiology 41(2):152-162.
  • Yong F.H., Tian L., Yu S., Cai T. and Wei L.J. (2016) Optimal stratification in outcome prediction using baseline information; Biometrika, 103.4: 817-828.
  • Castro V.M., Dligach D., Finan S., Yu S., Can A., Abd-El-Barr M., Gainer V.S., Shadick N.A., Murphy S.N., Cai T., Savova G., Weiss S.T., Du R. (2017) Large-scale identification of subjects with cerebral aneurysms using natural language processing. Neurology 88(2),164-168.
  • Yu S., Chakrabortty A., Liao K.P., Cai T., Ananthakrishnan A.N., Gainer V.S., Churchill S.E., Szolovits P., Murphy S.N., Kohane I.S., Cai T. (2017) Surrogate-assisted Feature Extraction for High-throughput Phenotyping. Journal of the American Medical Informatics Association 24(el), e143-e149

 

2015.7-2016.7
  • Shao Q. and Yang L. (2016) Oracally effcient estimation and consistent model selection for auto-regressive moving average time series with trend. Journal of the Royal Statistical Society Series B. DOI: 10.1111/rssb.12170.
  • Wang J., Wang S., and Yang L. (2016) Simultaneous confdence bands for the distribution function of a fnite population and its superpopulation. TEST 25(4), 692-709. 
  • Zheng S., Liu R., Yang L. and Härdle W. (2016) Statistical inference for generalized additive models: simultaneous confdence corridors and variable selection. TEST  25(4), 607-626. 
  • Yang M., Xue L. and Yang L. (2016) Variable selection for additive model via cumulative ratios of empirical strengths total. Journal of Nonparametric Statistics 28(3), 595-616.
  • Wu H. and Zhu Y. (2016) Deconvolution of base pair level RNA-Seq read counts for quantification of transcript expression levels. Annals of Applied Statistics. (To Appear)
  • 邓柯，陈孟裕，金锋，焦阳，丛林晔，罗季阳，殷杰（2016）中国进口食品风险评估的统计学方法。 《数理统计与管理》 ，已接收。
  • Deng K., Bol P.K., Li K.J., and Liu J.S. (2016) On unsupervised Chinese text mining. Online published in Proceedings of the National Academy of Sciences of USA. DOI: 10.1073/pnas.1516510113.
  • Zang C, Wang T., Deng K., et al (2016) High-dimensional genomic data bias correction and data integration using MANCIE. Online published in Nature Communications. DOI: 10.1038/ncomms11305.
  • Deng K., Li Y., Zhu W., and Liu J.S. (2016) Fast parameter estimation in loss tomography for networks of general topology. Online published in Annals of Applied Statistics. DOI: 10.1214/15-AOAS883
  • Li D., Ling S. and Zakoïan J.M. (2015) Asymptotic inference in multiple-threshold double autoregressive models. Journal of Econometrics 189, 415-427.
  • Li D., Ling S., and Zhang R.M. (2016) On a threshold double autoregressive model. Journal of Business & Economic Statistics 34, 68-80.
  • Li D., and Tong H. (2016) Nested sub-sample search algorithm for estimation of threshold models. Statistica Sinica. 26，4, 1543-1554.
  • Liu F., Li D., and Kang X.M. (2016) Sample path properties of an explosive double autoregressive model.Econometric Reviews. (To Appear)
  • Evans B., Gloria-Soria A., Hou L., McBride C., Bonizzoni M., Zhao H., Powell J. (2015) A multipurpose,high-throughput single-nucleotide polymorphism chip for the Dengue and Yellow Fever Mosquito, Aedes aegyptiG3, 3(5): 711-718.
  • Castro V., Shen Y., Yu S., Finan S., Pau C.T., Gainer V., Keefe C.C., Savova G., Murphy S.N., Cai T., Welt CK.(2015) Identifcation of subjects with polycystic ovary syndrome using electronic health records. Reproductive Biology and Endocrinology 13(1):1.
  • Cai T., Giannopoulos A.A., Yu S., Kelil T., Ripley B, Kumamaru K.K., Rybicki F.J., and Mitsouras D.*. (2016) Natural Language Processing Technologies in Radiology Research and Clinical Applications. RadioGraphics, 36(1): 176-191.