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2017
Cai, S., Chen, J. & Zidek, J.V., 2017. Hypothesis testing in the presence of multiple samples under density ratio models. Statistica Sinica, 27, pp.716–783.
Islam, N. et al., 2017. Incidence, risk factors, and prevention of hepatitis C reinfection: a population-based cohort study. The Lancet Gastroenterology & Hepatology, 2, pp.200–210.
McDonald, D.J., 2017. Minimax Density Estimation for Growing Dimension A. Singh & Zhu, J. , eds. Proceedings of the Twentieth International Conference on Artificial Intelligence and Statistics (AISTATS), 54, pp.194–203. Available at: http://proceedings.mlr.press/v54/mcdonald17a.html.
Panagiotelis, A. et al., 2017. Model selection for discrete regular vine copulas. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 106, pp.138-152.
Hua, L. & Joe, H., 2017. Multivariate dependence modeling based on comonotonic factors. Journal of Multivariate Analysis, 155, pp.317-333.
Béliveau, A. et al., 2017. Network meta-analysis of disconnected networks: How dangerous are random baseline treatment effects?. Research synthesis methods, 8, pp.465–474.
McDonald, D.J., Shalizi, C.Rohilla & Schervish, M., 2017. Nonparametric risk bounds for time-series forecasting. Journal of Machine Learning Research, 18, pp.1–40. Available at: http://www.jmlr.org/papers/v18/13-336.html.
Joe, H., 2017. Parametric copula families for statistical models. In M. Ubeda-Flores et al., eds. Copulas and Dependence Models with Applications: Contributions in Honor of Roger B. Nelsen. Copulas and Dependence Models with Applications: Contributions in Honor of Roger B. Nelsen. Berlin: Springer, pp. 119–134. Available at: https://link.springer.com/book/10.1007/978-3-319-64221-5.
Bouchard-Côté, A., Doucet, A. & Roth, A., 2017. Particle Gibbs split-merge sampling for Bayesian inference in mixture models. Journal of Machine Learning Research, 18, pp.1–39.
Vanetti, P. et al., 2017. Piecewise Deterministic Markov Chain Monte Carlo. arXiv, 1707.05296.
Zhai, Y. & Bouchard-Côté, A., 2017. A Poissonian model of indel rate variation for phylogenetic tree inference. Systematic Biology, (Accepted).
Zhai, Y. & Bouchard-Côté, A., 2017. A Poissonian model of indel rate variation for phylogenetic tree inference. Systematic Biology, 66, pp.698–714.
Lee, W. et al., 2017. Pre-averaged kernel estimators for the drift function of a diffusion process in the presence of microstructure noise. Statistical Inference for Stochastic Processes, 20(2).
Khalili, A., Chen, J. & , , 2017. Regularization in regime-switching Gaussian autoregressive models. The Canadian Journal of Statistics, 45, p.374.
McPherson, A. et al., 2017. ReMixT: clone-specific genomic structure estimation in cancer. Genome Biology, 18.
Homrighausen, D. & McDonald, D.J., 2017. Risk consistency of cross-validation for lasso-type procedures. Statistica Sinica, 27, pp.1017–1036. Available at: http://dx.doi.org/10.5705/ss.202015.0355.
Boente, G., Martínez, A. & Salibian-Barrera, M., 2017. Robust estimators for additive models using backfitting. Journal of Nonparametric Statistics, 29, pp.744-767. Available at: https://doi.org/10.1080/10485252.2017.1369077.

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