Lee, T.Yoon & Zidek, J.V., 2020. Scientific versus statistical modelling: a unifying approach,

Sadatsafavi, M. et al., 2020. Should the number of acute exacerbations in the previous year be used to guide treatments in COPD? . European Journal of Epidemiology, 35, p.To appear.

Zhu, P., Bouchard-Côté, A. & Campbell, T., 2020. Slice Sampling for General Completely Random Measures. In Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI). Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI). pp. 699–708.

Yang, Z. & Chen, J., 2020. Small area mean estimation after effect clustering. Journal of Applied Statistics, 47, pp.602–623.

Thomas, M.L. et al., 2020. Spatio-temporal downscaling for continental scale estimation of air pollution concentrations. Journal of the Royal Statistical Society: Series C, p.Submitted.

Yu, X., Li, S. & Chen, J., 2020. A three-parameter logistic regression model. Statistical Theory and Related Fields, pp.1–10.

Cooke, R.M., Joe, H. & Chang, B., 2020. Vine copula regression for observational studies. ASTA-Advances in Statistical Analysis, 104, pp.141-167.

Högg, T. et al., 2019. Adjusting for differential misclassification in matched case-control studies utilizing health administrative data. Statistics in Medicine, 38, pp.3669-3681.

Khodadadi, A. & McDonald, D.J., 2019. Algorithms for Estimating Trends in Global Temperature Volatility. In P. V. Hentenryck & Zhou, Z. - H. , eds. Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19). Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19). Association for the Advancement of Artificial Intelligence. Available at: https://doi.org/10.1609/aaai.v33i01.3301614.

Wang, L., Wang, S. & Bouchard-Côté, A., 2019. An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics. Systematic Biology, 69, pp.155–183.

Wang, L., Wang, S. & Bouchard-Côté, A., 2019. An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics. Systematic Biology, (Accepted).

Chang, B. et al., 2019. AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks. In International Conference on Learning Representations. International Conference on Learning Representations. Available at: https://openreview.net/forum?id=ryxepo0cFX.

Yang, C.-H., Zidek, J.V. & Wong, S.W.K., 2019. Bayesian analysis of accumulated damage models in lumber reliability. Technometrics, 61, pp.1-14.

Park, Y. et al., 2019. Causal Mediation Analysis Leveraging Multiple Types of Summary Statistics Data.

al., K.R.Campbell, 2019. clonealign: statistical integration of independent single-cell RNA & DNA-seq from human cancers. Genome Biology, (Accepted).

Campbell, K. & al., et, 2019. clonealign: statistical integration of independent single-cell RNA and DNA-seq from human cancers. Genome Biology, 20, pp.1–12.

Karim, M.E. et al., 2019. Comparison of statistical approaches dealing with time-dependent confounding in drug effectiveness studies. Statistical Methods in Medical Research, 28, pp.323-324 .

Chen, J. et al., 2019. Contemporary Theory and Practice of Survey Sampling: A Celebration of Research Contributions of JNK Rao.

Thomas, M.L. et al., 2019. Data integration for high-resolution, continental-scale estimation of air pollution concentrations. arXiv preprint arXiv:1907.00093.

Thomas, M.L. et al., 2019. Data integration for high-resolution, continental-scale estimation of air pollution concentrations. arXiv preprint arXiv:1907.00093.

Chen, J. & Feng, Z., 2019. A discussion of ‘prior-based Bayesian information criterion’. Statistical Theory and Related Fields, pp.1–3.

Wong, S.W.K. & Zidek, J.V., 2019. The duration of load effect in lumber as stochastic degradation. IEEE Transactions on Reliability, pp.410-419.

Zolaktaf, S. et al., 2019. Efficient Parameter Estimation for DNA Kinetics Modeled as Continuous-Time Markov Chains. In The 25th International Conference on DNA Computing and Molecular Programming. The 25th International Conference on DNA Computing and Molecular Programming. pp. 80–99.

Loucks, C.M. et al., 2019. EFHC1, implicated in juvenile myoclonic epilepsy, functions at the cilium and synapse to modulate dopamine signaling. Elife, 8, p.e37271.

Deligiannidis, G., Bouchard-Côté, A. & Doucet, A., 2019. Exponential Ergodicity of the Bouncy Particle Sampler. Annals of Statistics, 47, pp.1268–1287.