[1] Ai, Mingyao; Li, Kang; Liu, Senmao; Lin, Dennis (2013). Balanced Incomplete Latin Square Designs, Journal of Statistical Planning and Inference,
143 (9), 1575-1582.
[2] An, B., Wang, H., Guo, J. (2013). Testing the statistical significance of an ultra-high dimensional naive Bayes classifier, Statistics and Its Interface,
2013, 223--229.
[3] An, B., Wang, H., Guo, J. (2013). Multivariate Regression Shrinkage and Selection by Canonical Correlation Analysis, Computational Statistics and
Data Analysis, 62, 93--107.
[4] Chen Peng and ZhangFuxi (2013), Limit theorems for the position of a tagged particle in the stirring-exclusion process, Frontiers of Mathematics
in China, 8 (3), Issue 3,479-496
[5] Chen, S. X. and Van Keilegom, I. (2013). Estimation in semiparametric models with missing data, Annals of the Institute of Statistical Mathematics,
65 , 785-805.
[6] Chen, S.X., Xu Zheng (2013). On smoothing estimation for seasonal time series with long cycles, Statistics and Its Interface, Volumn6, 435-447.
[7] Chen, S.X., Peng, L. and C. L. Yu (2013). Parameter Estimation and Model Testing for Markov Processes via Conditional Characteristic Functions,
Bernoulli, 19, 228-251.
[8] Chen, S.X., Tang, C.Y. and J. Qin (2013). Mann-Whitney Test with Adjustments to Pre-treatment Variables for Missing Values and Observational
Study, Journal of the Royal Statistical Society, Series B., 75, 81-102.
[9] Cui Wei, Yang Jingping and WuLan (2013). Optimal reinsurance minimizing the distortion risk measure under general reinsurance premium prin-ciples, Insurance: Mathematics and Economics, Vol. 53(1), 74–85.
[10] Deng, W., Geng, Z. and Li, H. (2013). Learning local directed acyclic graphs based on multivatriate time series data, Annals of Applied Statistics,
7, 1663-1683.
[11] Deng, W., Geng, Z. and Luo, P. (2013). Identifiability of intermediate variables on causal paths, Front. Math. China, 8, 517-539.
[12] He Yangbo, Jia Jinzhu and Yu Bin (2013). Reversible MCMC on Markov equivalence classes of sparse directed acyclic graphs, The Annals of
Statistics, Vol 41, 1742-1779.
[13] Ho, C. Wang W. and Yu J. (2013). Growth Spillover through Trade: A Spatial Dynamic Panel Data Approach, Economics Letters, 120, 45-45.
[14] Jia Jinzhu, Rohe Karl and Yu Bin (2013). The Lasso under Heteroscaddasticity, Statistica Sinica,Vol 23, pp 99–118.
[15] Jiang, Q., Wang, H., Xia, Y., and Jiang, G. (2013). On a principal varying coefficient model, Journal of the American Statistical Association, 108,
228--236.
[16] Kim Tae-Min, Xi Ruibin, Lovelace J. Luquette, Richard W. Park, Mark D. Johnson, and Peter J. Park (2013). Functional genomic analysis of
chromosomal ab-errations in a compendium of 8000 cancer genomes, Genome Res. 2013 23: 217-227.
[17] Lee, L.F., and Yu J. (2013). Near Unit Root in the Spatial Autoregressive Model, Spatial Economic Analysis , 8, 314-351.
[18] Li Chenxu (2013). Maximum-Likelihood Estimation For Diffusion Processes Via Closed-Form Density Expansions , The Annals of Statistics, Vol.
41, No. 3, 1350–1380.
[19] Li Y, Wang X, Zheng H, Wang C, Minvielle S, Magrangeas F, Avet-.(2013). Classify hyperdiploidy status Loiseau H, Shah PK, Zhang Y, Munshi
NC, Li Cof multiple myeloma patients using gene expression profiles, PLoS One. 2013. 8(3):e58809.
[20] Liu Rongli, Ren Yan-Xia and Song Renming (2013). Strong law of large numbers for a class of superdiffusions, Acta Applicanda Mathematicae,
123(1), 73-97.
[21] Liang Peng; Qian, Linyi; Yang Jingping (2013). Weighted estimation of the dependence function for an extreme-value distribution, Bernoulli, Vol.
19(2), 492-520.
[22] Kuroda, M. H., Hashiguchi, S., Nakagawa and Geng, Z. (2013). MCMC using Markov bases for computing p-values in decomposable log-linear
models, Computational Statistics, 28, 831-850.
[23] 秦昕、徐敏亚 (2013). “如何管理新生代农民工”,《商界》,02月刊.
[24] 秦昕、徐敏亚 (2013). “新生代农民工: 从梦想终结到梦想驱动”《商界评论》,02月刊.
[25] Samur MK, Shah PK, Wang X, Minvielle S, Magrangeas F, Avet-Loiseau H, Munshi NC, Li C.(2013). The shaping and functional consequences
of the dosage effect landscape in multiple myeloma, BMC Genomics. 2013. 14(1):672.
[26] Samur MK, Yan Z, Wang X, Cao Q, Munshi NC, Li C, Shah PK. (2013). canEvolve: A web portal for integrative oncogenomics, PLoS One, 2013.
8(2):e56228.
[27] Song Kai, Ren Jie, Zhai Zhiyuan, Liu Xuemei, Deng Minghua and Sun Fengzhu (2013). Alignment-Free Sequence Comparison Based on Next-Generation Sequencing Reads, Journal of Computational Biology, 20(2), 64-79.
[28] Su Naifang, Minping Qian and DengMinghua (2013). Integrative Approaches for microRNA Target Prediction: Combining Sequence Information
and the Paired mRNA and miRNA Expression Profiles, Current Bioinformatics, 8, 37-45.
[29] Wang, C., Zhou, Y. and Geng, Z. (2013). Discovering causes and effects of a given node in Bayesian networks, Front. Math. China, 8, 643-663.
[30] Wang Fugui, Chen Rui, Ji Dong, Bai Shunong, Qian Minping and Deng Minghua, (2013). Adjustment method for microarray data generated using
two-cycle RNA labeling protocol, BMC Genomics 2013.
[31] Wang L, Zheng W, Zhao H, Deng M (2013). Statistical Analysis Reveals Co-Expression Patterns of Many Pairs of Genes in Yeast Are Jointly
Regulated by Interacting Loci, PLoS Genet 9(3): e1003414. doi:10.1371/journal.pgen.1003414
[32] Wang X, Yan Z, Fulciniti M, Li Y, Gkotzamanidou M, Amin SB, Shah PK, Zhang Y, Munshi NC, Li C.(2013). Transcription factor-pathway co-expression analysis reveals cooperation between SP1 and ESR1 on dysregulating cell cycle arrest in non-hyperdiploid multiple myeloma, Leukemia.
[33] Wang, Ruodu; Peng, Liang; Yang Jingping (2013). Bounds for the sum of dependent risks and worst Value-at-Risk with monotone marginal
densities, Finance and Stochastics,Vol.17 (2), 395-417.
[34] Wang, Ruodu; Peng, Liang; Yang Jingping (2013). Jackknife empirical likelihood for parametric copulas, Scandinavian Actuarial Journal, 2013(5), 325-339.
[35] Wu, L., Yang, Y., Liu, H. (2013). Nonnegative-lasso and application in index tracking, Computational Statistics & Data Analysis, 70, 116-126.
[36] Xie, Siyuan; Yang Jingping; Zhou, Shulin (2013). Numerical algorithms for Panjer recursion by applying Bernstein approximation, Frontiers of
Mathematics in China, 8(5), 1197-1226.
[37] 徐敏亚、刘古权、李瑞(2013). “大数据对组织变革的影响” ,《企业管理》,09 月刊.
[38] Xu Qianqian, Xiong Jiechao, Huang Qingming, Yao Yuan (2013).“Robust Evaluation for Quality of Experience in Crowdsourcing”, in Proceed-
ings of ACM Multimedia Conference, Barcelona, Catalunya, Spain, pp43-52, Oct. 21-25, 2013.
[39] Xue Xiaofeng (2013). Contact processes with random connection weights on regular graphs, Physica A: Statistical Mechanics and its Applica-tions, 392(20): 4749-4759.
[40] Yang Lixing, Lovelace J. Luquette, Nils Gehlenborg, Xi Ruibin, Psalm S. Haseley, Chih-Heng Hsieh, Chengsheng Zhang, Xiaojia Ren, Alexei
Protopopov, Lynda Chin, Raju Kucherlapati, Charles Lee, and Peter J. Park (2013). Diverse Mechanisms of Somatic Structural Variations in Human
Cancer Genomes, Cell 153, 919–929.
[41] Yu., J and G. Zhu (2013). How Uncertain is Household Income in China, Economics Letters, 120, 74-78.
[42] Zhang, Q., Li, D., and Wang, H. (2013). A Note on Tail Dependence Regression, Journal of Multivariate Analysis, 120, 163--172.
[43] Zhao, J., Leng, C., Lexin, Li., and Wang, H. (2013). High Dimensional Influence Measure, The Annals of Statistics, 41(5), 2639--2667.
[44] Zhong Ping Shou, Chen, S. X. and Xu Minya (2013). Tests alternative to higher criticism for high dimensional means under sparsity and column-wise dependence, Annals of Statistics, 41, 2820-2851.
