Wu, L., Liu, W. & Hu, X.J., 2010. Joint Inference on HIV Viral Dynamics and Immune Suppression in Presence of Measurement Errors. Biometrics, 66, pp.327–335. Available at: http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2009.01308.x/abstract.

Sankararaman, S., Bouchard-Côté, A. & Jordan, M.I., 2010. Joint Probabilistic Modeling of Languages and Genes. In Society for Molecular Biology and Evolution. Society for Molecular Biology and Evolution.

Cadigan, N.G. & Chen, J., 2010. Kernel regression estimators for nonparametric model calibration in survey sampling. Journal of Statistical Theory and Practice, 4, pp.1–25.

Woolcott, C.G. et al., 2010. Mammographic density change with 1 year of aerobic exercise among postmenopausal women: a randomized controlled trial. Cancer Epidemiol. Biomarkers Prev., 19, pp.1112–1121.

Balkema, A.A., Embrechts, P. & Nolde, N., 2010. Meta densities and the shape of their sample clouds. Journal of Multivariate Analysis, 101, pp.1738–1754.

Hosseini, R., Le, N.D. & Zidek, J.V., 2010. Model selection for the binary dichotomized temperature processes.

Yan, G., Welch, W.J. & Zamar, R.H., 2010. Model-based linear clustering. Canadian Journal of Statistics, 38, pp.716–737. Available at: http://onlinelibrary.wiley.com/doi/10.1002/cjs.10082/full.

Yan, G., Welch, W.J. & Zamar, R.H., 2010. Model-based linear clustering. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 38, pp.716-737.

Dou, Y., Le, N.D. & Zidek, J.V., 2010. Modeling hourly ozone concentration fields. The Annals of Applied Statistics, 4, pp.1183–1213.

Zidek, J.V. & Zimmerman, D.L., 2010. Monitoring network design. Handbook of Spatial Statistics, pp.131–148.

Zhu, R. & Joe, H., 2010. Negative binomial time series models based on expectation thinning operators. Journal of Statistical Planning and Inference, 140, pp.1874-1888.

Clarren, S.K. et al., 2010. Normal distribution of palpebral fissure lengths in Canadian school age children. Can J Clin Pharmacol, 17, pp.67–78.

Lee, D. et al., 2010. A note on the ordered means of exponential family. Far East Journal of Theoretical Statistics, 31, pp.69–75.

Berg-Kirkpatrick, T. et al., 2010. Painless unsupervised learning with features. In Proceedings of the North American Chapter of the Association for Computational Linguistics (NAACL10). Proceedings of the North American Chapter of the Association for Computational Linguistics (NAACL10). pp. 582–590.

Brasher, P.M. & Brant, R.F., 2010. Pictures worthy of a thousand words. Can J Anaesth, 57, pp.961–965.

Hull, R.D., Liang, J. & Brant, R., 2010. Pooled analysis of trials may, in the presence of heterogeneity inadvertently lead to fragile conclusions due to the importance of clinically relevant variables being either hidden or lost when the findings are pooled. Thromb. Res., 126, pp.164–165.

Cai, S., Zidek, J.V. & Newlands, N., 2010. Predicting phenological events using event-history analysis.

Cai, S., Zidek, J.V. & Newlands, N., 2010. Predicting Sequences of Progressive Events Times with Time-dependent Covariates.

Gustafson, P. & McCandless, L.C., 2010. Probabilistic approaches to better quantifying the results of epidemiologic studies. International Journal of Environmental Research and Public Health, 7, pp.1520-1539.

Bouchard-Côté, A., 2010. Probabilistic Models of Evolution and Language Change. UC Berkeley.

Freue, G.V.Cohen et al., 2010. Proteomic signatures in plasma during early acute renal allograft rejection. Molecular & Cellular Proteomics, 9, pp.1954–1967.

Carrillo, I.A., Chen, J. & Wu, C., 2010. The pseudo-GEE approach to the analysis of longitudinal surveys. Canadian Journal of Statistics, 38, pp.540–554.

Kokel, D. et al., 2010. Rapid behavior-based identification of neuroactive small molecules in the zebrafish. NATURE CHEMICAL BIOLOGY, 6, pp.231-237.

Kokel, D. et al., 2010. Rapid behavior-based identification of neuroactive small molecules in the zebrafish. Nature chemical biology, 6, pp.231–237.

Polman, C.H. et al., 2010. Recommendations for clinical use of data on neutralising antibodies to interferon-beta therapy in multiple sclerosis. Lancet Neurology, 9, pp.740-750.