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Liu, Y., Shaddick, G. & Zidek, J.V., 2015. incorporating high-dimensional exposure modelling into studies of air pollution and health. Statistics in Biosciences, p.Accepted.

Roth, A. et al., 2015. Inference of clonal genotypes from single cell sequencing data. In HitSeq. HitSeq.

Chen, J., 2015. The joy of proofs in statistical research. Canadian Journal of Statistics, 43, pp.481–497.

Li, S. et al., 2015. Likelihood Ratio Test for Multi-Sample Mixture Model and Its Application to Genetic Imprinting. Journal of the American Statistical Association, 110, pp.867–877.

Joe, H., 2015. Markov count time series models with covariates. In R. A. Davis et al., eds. Handbook of Discrete-Valued Time Series. Handbook of Discrete-Valued Time Series. Boca Raton, FL: Chapman & Hall/CRC, pp. 29–49. Available at: http://www.crcpress.com/product/isbn/9781466577732.

Crane, J.M. et al., 2015. Maternal and perinatal outcomes of pregnancies delivered at 23 weeks' gestation. J Obstet Gynaecol Can, 37, pp.214–224.

Fairbrother, N. et al., 2015. Maternal thoughts of harm in response to infant crying: an experimental analysis. Arch Womens Ment Health, 18, pp.447–455.

Qiu, J. & WU, L.A.N.G., 2015. A moving blocks empirical likelihood method for longitudinal data. Biometrics, 71, pp.616–624. Available at: http://onlinelibrary.wiley.com/doi/10.1111/biom.12317/abstract.

Shirani, A. et al., 2015. Multiple Sclerosis in Older Adults: The Clinical Profile and Impact of Interferon Beta Treatment. BioMed research international, 2015.

Shirani, A. et al., 2015. Multiple sclerosis in older adults: the clinical profile and impact of interferon beta treatment. BioMed Research International, 2015, p.ID451912, 11 pages.

Lavoie, P.M. et al., 2015. Oral glucose during targeted neonatal echocardiography: is it useful?. Arch. Dis. Child. Fetal Neonatal Ed., 100, pp.F374–375.

Bouchard-Côté, A., Doucet, A. & Roth, A., 2015. Particle Gibbs split-merge sampling for Bayesian inference in mixture models. Journal of Machine Learning Research, (Accepted).

Bouchard-Côté, A., Doucet, A. & Roth, A., 2015. Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models. arXiv, 1508.02663.

Zhao, Y. et al., 2015. Personalized activity index, a new safety monitoring tool for multiple sclerosis clinical trials. Multiple Sclerosis Journal – Experimental, Translational and Clinical, 1, pp.1-15. Available at: http://mso.sagepub.com/content/1/2055217315577829.

Hartung, H.P. et al., 2015. Predictors of disease activity in 857 patients with MS treated with interferon beta-1b. Journal of Neurology, 262, pp.2466-2471.

Hartung, H.-P. et al., 2015. Predictors of disease activity in 857 patients with MS treated with interferon beta-1b. Journal of neurology, 262, pp.2466–2471.

Joe, H. et al., 2015. Preface to special issue on high-dimensional dependence and copulas. Journal of Multivariate Analysis, 138, pp.1-3.

Wong, S.W.K. et al., 2015. Quantifying uncertainty in lumber grading and strength prediction: a Bayesian approach. Technometrics, 58, pp.236-243.

Hall, W.A. et al., 2015. A randomized controlled trial of an intervention for infants' behavioral sleep problems. BMC Pediatr, 15, p.181.

Lavoie, P.M. et al., 2015. A Randomized Controlled Trial of the Use of Oral Glucose with or without Gentle Facilitated Tucking of Infants during Neonatal Echocardiography. PLoS ONE, 10, p.e0141015.

Agostinelli, C. et al., 2015. Rejoinder on: Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination. TEST, 24, pp.484-488.

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Wang, L., Chen, J. & Pu, X., 2015. Resampling calibrated adjusted empirical likelihood. Canadian Journal of Statistics, 43, pp.42–59.

Etminan, M., Luo, H. & Gustafson, P., 2015. Risk of intracranial hypertension with intrauterine levonorgestrel. Therapeutic advances in drug safety, 6, pp.110–113.