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On November 28,2016, Dr.Zhixiang Lin from Stanford University visited the Center and gave a talk entitled AC-PCA: simultaneous dimension reduction and adjustment for confounding variation.

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On November 28,2016, Dr.Zhixiang Lin from Stanford University visited the Center and gave a talk entitled AC-PCA: simultaneous dimension reduction and adjustment for confounding variation.

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  1. Publications

  • 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. (To Appear)
  • Wang J., Wang S., and Yang L. (2016) Simultaneous confdence bands for the distribution function of a fnite population and its superpopulation. TEST. DOI: 10.1007/s11749-016-0491-5. (To Appear)
  • Zheng S., Liu R., Yang L. and Härdle W. (2016) Statistical inference for generalized additive models: simultaneous confdence corridors and variable selection. TEST. DOI 10.1007/s11749-016-0480-8. (To Appear)
  • 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)
  • Deng K.,Chen Mengyu, Jin Feng, Jiao Yang, Cong Linye, Luo Jiyang, Yin Jie (2016), Statistical Methods for Assessing Safety Risk of Imported Foods in China, Journal of Applied Statistics and Management. (To appear)
  • 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 Annuals 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. (To Appear)
  • 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 aegypti G3, 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., Mitsouras D. (2016) Natural language processing technologies in radiology research and clinical applications.RadioGraphics 36(1):176-191.

2. Research Projects

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3. Academic Awards

Prof. Ke Deng delivered a specially invited talk on statistics at the 12th National Conference of Chinese Mathematical Society.

4. Patents

Search engine patent: “A method and device for information retrieval”
Function: Accurate identification of electronic medical records by semantic analysis of the records and the query.
Inventor: Yu Sheng. Patent ID: ZL201310200430.3. Grant date: June 1st, 2016.

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On November 14th, 2016, Prof. Minping Qian from Peking University visited the Center and gave a talk entitled From two stories seeing the opportunity and challenging from Biological big data.

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On November 14th, 2016, Prof. Minping Qian from Peking University visited the Center and gave a talk entitled From two stories seeing the opportunity and challenging from Biological big data.

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