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2016
Tomal, J.H., Welch, W.J. & Zamar, R.H., 2016. Exploiting Multiple Descriptor Sets in QSAR Studies. Journal of chemical information and modeling, 56, pp.501–509. Available at: http://pubs.acs.org/doi/abs/10.1021/acs.jcim.5b00663.
Zhai, Y. & Bouchard-Côté, A., 2016. Inferring history of human populations using single-nucleotide polymorphism. Annals of Applied Stat, 10, pp.2047–2074.
Zhai, Y. & Bouchard-Côté, A., 2016. Inferring history of human populations using single-nucleotide polymorphism. Annals of Applied Statistics, 10, pp.2047–2074.
Kepplinger, D., Salibian-Barrera, M. & Freue, G.V.Cohen, 2016. Initial estimators for regularized robust methods in high-dimensional settings. In 22nd International Conference on Computational Statistics. 22nd International Conference on Computational Statistics.
Shaddick, G., Zidek, J.V. & Liu, Y., 2016. Mitigating the effects of preferentially selected monitoring sites for environmental policy and health risk analysis. Spatial and Spatio-temporal epidemiology, 18, pp.44-52.
Lau, K., Salibian-Barrera, M. & Lampe, L., 2016. Modulation recognition in the 868 MHz band using classification trees and random forests. {AEU} - International Journal of Electronics and Communications, 70, pp.1321 - 1328. Available at: http://www.sciencedirect.com/science/article/pii/S1434841116303430.
Chen, J. et al., 2016. Monitoring test under nonparametric random effects model. arXiv preprint arXiv:1610.05809.
Chen, J. et al., 2016. Monitoring test under nonparametric random effects model. arXiv preprint arXiv:1610.05809.
Joe, H. & Sang, P., 2016. Multivariate models for dependent clusters of variables with conditional independence given aggregation variables. Computational Statistics & Data Analysis, 97, pp.114-132.
Homrighausen, D. & McDonald, D.J., 2016. On the Nyström and Column-Sampling Methods for the Approximate Principal Components Analysis of Large Data Sets. Journal of Computational and Graphical Statistics, 25, pp.344–362. Available at: http://dx.doi.org/10.1080/10618600.2014.995799.
Mostafavi, S. et al., 2016. Parsing the Interferon Transcriptional Network and Its Disease Associations. Cell, 164, pp.564–578.
Rennison, D.J. et al., 2016. Rapid adaptive evolution of colour vision in the threespine stickleback radiation. Proceedings of the Royal Society of London B: Biological Sciences, 283. Available at: http://rspb.royalsocietypublishing.org/content/283/1830/20160242.
Khalili, A., Chen, J. & Stephens, D.A., 2016. Regularization in Regime-Switching Gaussian Autoregressive Models. In Advanced Statistical Methods in Data Science. Advanced Statistical Methods in Data Science. Springer Singapore, pp. 13–34.
Leung, A., Zhang, H. & Zamar, R., 2016. Robust regression estimation and inference in the presence of cellwise and casewise contamination. Computational Statistics & Data Analysis.
Salibian-Barrera, M., Van Aelst, S. & Yohai, V.J., 2016. Robust tests for linear regression models based on tau-estimates. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 93, pp.436-455.
Kondo, Y., Salibian-Barrera, M. & Zamar, R., 2016. RSKC: An R Package for a Robust and Sparse K-Means Clustering Algorithm. Journal of Statistical Software, 72, pp.1–26. Available at: https://www.jstatsoft.org/index.php/jss/article/view/v072i05.
Chen, J., Li, P. & Liu, Y., 2016. Sample-size calculation for tests of homogeneity. Canadian Journal of Statistics, 44, pp.82–101.

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