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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.
Boente, G. & Salibian-Barrera, M., In Press. Robust functional principal components for sparse longitudinal data. Metron.
Campbell, T. et al., In Press. Truncated random measures. Bernoulli.
2021
Wang, Y., Le, N.D. & Zidek, J.V., 2021. Approximately Optimal Subset Selection for Statistical Design and Modelling. Journal of Statistical Computation and Simulation, pp.1-13.
Chen, J. et al., 2021. Composite empirical likelihood for multisample clustered data. J Nonparametric Statistics, p.Accepted Apr 2021.
Pan, S. et al., 2021. Ellipse Detection and Localization with Application to Knots in Sawn Lumber I. 2021 IEEE Winter Conference on Applications of Computer Vision (WACV).
Martínez, A. & Salibian-Barrera, M., 2021. RBF: An R package to compute a robust backfitting estimator for additive models. The Journal of Open Source Software, 6(60).
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.
2020
Wang, Y., Le, N.D. & Zidek, J.V., 2020. Approximately Optimal Spatial Design: How Good is it?. Spatial Statistics, p.To appear.
Chang, B. & Joe, H., 2020. Copula diagnostics for asymmetries and conditional dependence. Journal of Applied Statistics, 47, pp.1587-1615.
Watson, J., 2020. CV.
Lee, T.Yoon, Zidek, J.V. & Heckman, N., 2020. Dimensional Analysis in Statistical Modelling. Statistical Science, p.Submitted.
Krupskii, P. & Joe, H., 2020. Flexible copula models with dynamic dependence and application to financial data. Econometrics and Statistics, 16, pp.148-167.
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.

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