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2014
Zhang, J. et al., 2014. Prinsimp. R JOURNAL, 6, pp.27-42.
Hollander, Z. et al., 2014. Proteomic biomarkers of recovered heart function. European journal of heart failure, 16, pp.551–559.
Roth, A. et al., 2014. PyClone: statistical inference of clonal population structure in cancer. Nature Methods, 11, pp.396–398.
Zidek, J.V. et al., 2014. Reducing estimation bias in adaptively changing monitoring networks with preferential site selection. The Annals of Applied Statistics, 8, pp.1640–1670.
Zidek, J.V., Shaddick, G. & Taylor, C.G., 2014. Reducing estimation bias in adaptively changing monitoring networks with preferential site selection. The Annals of Applied Statistics, 8, pp.1640–1670.
Hua, L., Joe, H. & Li, H., 2014. Relations between hidden regular variation and the tail order of copulas. Journal of Applied Probability, 51, pp.37-57.
Reich, D.S. et al., 2014. Sample-size calculations for short-term proof-of-concept studies of tissue protection and repair in MS lesions via conventional clinical imaging. In MULTIPLE SCLEROSIS JOURNAL. MULTIPLE SCLEROSIS JOURNAL. SAGE PUBLICATIONS LTD 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND, pp. 284–284.
Bouchard-Côté, A., 2014. Sequential Monte Carlo (SMC) for Bayesian phylogenetics. In M. - H. Chen, Kuo, L. , & Lewis, P. O. (eds.), eds. Bayesian phylogenetics: methods, algorithms, and applications. Bayesian phylogenetics: methods, algorithms, and applications. pp. 163–186.
Coia, V. & Huang, M.Ling, 2014. A Sieve model for extreme values. Journal of Statistical Computation and Simulation, 84, pp.1692–1710.
Xu, C. & Chen, J., 2014. The Sparse MLE for Ultrahigh-Dimensional Feature Screening. Journal of the American Statistical Association, 109, pp.1257–1269.
Cai, S. et al., 2014. Statistical modeling and forecasting of fruit crop phenology under climate change. Environmetrics, 25, pp.621–629.
Nolde, N. & Parker, G., 2014. Stochastic analysis of life insurance surplus. INSURANCE MATHEMATICS & ECONOMICS, 56, pp.1-13.
Hua, L. & Joe, H., 2014. Strength of tail dependence based on conditional tail expectation. Journal of Multivariate Analysis, 123, pp.143-159.
de Souza, C.P.E. & Heckman, N.E., 2014. Switching nonparametric regression models. JOURNAL OF NONPARAMETRIC STATISTICS, 26, pp.617-637.
Mostafavi, S. et al., 2014. Variation and Genetic Control of Gene Expression in Primary Immunocytes across Inbred Mouse Strains. JOURNAL OF IMMUNOLOGY, 193, pp.4485-4496.
Ascherio, A. et al., 2014. Vitamin D as an early predictor of multiple sclerosis activity and progression. JAMA neurology, 71, pp.306–314.

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