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In Press
Campbell, T., Kulis, B. & How, J., In Press. Dynamic clustering algorithms via small-variance analysis of Markov chain mixture models. IEEE Transactions on Pattern Analysis and Machine Intelligence.
Zhu, G. & Chen, J., In Press. Multi-parameter One-Sided Monitoring Tests. Technometrics.
Lennox, R.J. et al., In Press. Optimizing marine spatial plans with animal tracking data. Canadian Journal of Fisheries and Aquatic Sciences.
Campbell, T. et al., In Press. Truncated random measures. Bernoulli.
Ju, X. & Salibian-Barrera, M., 2021. Robust Boosting for Regression Problems. Computational Statistics and Data Science, 153. Available at: https://arxiv.org/abs/2002.02054.
Wang, Y., Le, N.D. & Zidek, J.V., 2020. Approximately Optimal Spatial Design: How Good is it?. Spatial Statistics, p.To appear.
Watson, J., 2020. CV.
Boente, G., Salibian-Barrera, M. & Vena, P., 2020. Robust estimation for semi-functional linear regression models. Computational Statistics and Data Science, 152. Available at: https://arxiv.org/abs/2006.16156.
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.
Surjanovic, S. & Welch, W.J., 2019. Adaptive Partitioning Design and Analysis for Emulation of a Complex Computer Code. arXiv preprint arXiv:1907.01181.
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.
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 .
Wang, Y., Le, N.D. & Zidek, J.V., 2019. Determinental point processes stochastic approximation for combinatorial optimization. Optimization Letters.