Research

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Publications by Department Members

2021

Syed S, Bouchard-Côté A, Deligiannidis G, Doucet A. Non-Reversible Parallel Tempering: a Scalable Highly Parallel MCMC Scheme. Journal of Royal Statistical Society, Series B. 2021; (Accepted).
Syed S, Romaniello V, Campbell T, Bouchard-Côté A. Parallel Tempering on Optimized Paths. In International Conference on Machine Learning (ICML). 2021.
Wang Y, Le ND, Zidek JV. Approximately Optimal Subset Selection for Statistical Design and Modelling. Journal of Statistical Computation and Simulation. 2021;: 1-13.
Zhang AGong, Chen J. Empirical likelihood ratio test on quantiles under a density ratio model. Electronic Journal of Statistics [Internet]. 2021; 15(2): 6191-6227. URL: https://doi.org/10.1214/21-EJS1943
Zhang Q, Chen J. Minimum Wasserstein Distance Estimator under Finite Location-scale Mixtures. arXiv preprint arXiv:2107.01323. 2021;.
Zhao T, Bouchard-Côté A. Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler. Journal of Machine Learning Research. 2021; 22: 1–41.

2020

Boente G, Salibian-Barrera M, Vena P. Robust estimation for semi-functional linear regression models. Computational Statistics and Data Science [Internet]. 2020; 152. DOI: 10.1016/j.csda.2020.107041 URL: https://arxiv.org/abs/2006.16156 Software: https://github.com/msalibian/RobustFPLM
Chen J, Li P, Liu G. Homogeneity testing under finite location-scale mixtures. Canadian Journal of Statistics. John Wiley & Sons, Inc. Hoboken, USA; 2020; 48: 670–684.
Cooke RM, Joe H, Chang B. Vine copula regression for observational studies. ASTA-Advances in Statistical Analysis. 2020; 104: 141-167. DOI: 10.1007/s10182-019-00353-5
Deligiannidis G, Paulin D, Bouchard-Côté A, Doucet A. Randomized Hamiltonian Monte Carlo as Scaling Limit of the Bouncy Particle Sampler and Dimension-Free Convergence Rates. Annals of Applied Probability. 2020; (Accepted).
Homrighausen D, McDonald DJ. Compressed and penalized linear regression. Journal of Computational and Graphical Statistics [Internet]. 2020; 29: 309–322. URL: https://doi.org/10.1080/10618600.2019.1660179
Karim ME, Tremlett H, Zhu F, Petkau J, Kingwell E. Dealing with treatment-confounder feedback and sparse follow-up in longitudinal studies - application of a marginal structural model in a multiple sclerosis cohort. . American Journal of Epidemiology. 2020; 189: To appear.
Krupskii P, Joe H. Flexible copula models with dynamic dependence and application to financial data. Econometrics and Statistics. 2020; 16: 148-167. DOI: 10.1016/j.ecosta.2020.01.005
Lee TYoon, Zidek JV. Scientific versus statistical modelling: a unifying approach. arXiv preprint arXiv:2002.11259. 2020 .
McDonald DJ. Book Review: Sufficient Dimension Reduction: Methods and Applications with R. Journal of the American Statistical Association [Internet]. 2020; 115. URL: https://doi.org/10.1080/01621459.2020.1759990
Pan S, Fan S, Wong SWK, Zidek JV, Rhodin H. Ellipse Detection and Localization with Applications to Knots in Sawn Lumber Images. arXiv preprint arXiv:2011.04844. 2020 .
Sadatsafavi M, McCormack J, Lee TY, Petkau J, Lynd L, Sin D. Should the number of acute exacerbations in the previous year be used to guide treatments in COPD? . European Journal of Epidemiology. 2020; 35: To appear.
Thomas ML, Shaddick G, Simpson D, de Hoogh K, Zidek JV. Spatio-temporal downscaling for continental scale estimation of air pollution concentrations. Journal of the Royal Statistical Society: Series C. 2020;: Submitted.
Wang Y, Le ND, Zidek JV. Approximately Optimal Spatial Design: How Good is it?. Spatial Statistics. 2020; 37: 100409.
Yang Z, Chen J. Small area mean estimation after effect clustering. Journal of Applied Statistics. Taylor & Francis; 2020; 47: 602–623.
Yu X, Li S, Chen J. A three-parameter logistic regression model. Statistical Theory and Related Fields. Taylor & Francis; 2020;: 1–10.
Zhu P, Bouchard-Côté A, Campbell T. Slice Sampling for General Completely Random Measures. In Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI). 2020. pp. 699–708.

2019

Chang B, Pan S, Joe H. Vine copula structure learning via Monte Carlo tree search. In: Chaudhuri K, Sugiyama M. 22ND International Conference on Artificial Intelligence and Statistics, Vol 89. 2019. pp. 353-361.
Chang B, Joe H. Prediction based on conditional distributions of vine copulas. Computational Statistics & Data Analysis. 2019; 139: 45–63.
Chang B, Pan S, Joe H. Vine Copula Structure Learning via Monte Carlo Tree Search. In International Conference on Artificial Intelligence and Statistics. 2019.
Chang B, Chen M, Haber E, Chi EH. AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks. In International Conference on Learning Representations [Internet]. 2019. URL: https://openreview.net/forum?id=ryxepo0cFX
Chang B, Joe H. Prediction based on conditional distributions of vine copulas. Computational Statistics & Data Analysis. 2019; 139: 45-63. DOI: 10.1016/j.csda.2019.04.015
Chen Z, Chen J, Zhang Q. Small area quantile estimation via spline regression and empirical likelihood. Survey Methodology 45-1. 2019; 45: 81–99.
Chen J, Liu Y. Small area quantile estimation. International Statistical Review. 2019; 87: S219–S238.
Chen J, Feng Z. A discussion of ‘prior-based Bayesian information criterion’. Statistical Theory and Related Fields. 2019;: 1–3.
Cohen-Freue GV, Kepplinger D, Salibian-Barrera M, Smucler E. Robust elastic net estimators for variable selection and identification of proteomic biomarkers. Annals of Applied Statistics [Internet]. 2019; 13(4): 2065-2090. DOI: 10.1214/19-AOAS1269 URL: http://dx.doi.org/10.1214/19-AOAS1269 Software: https://cran.r-project.org/package=pense
Cornish R, Vanetti P, Bouchard-Côté A, Deligiannidis G, Doucet A. Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets. In International Conference on Machine Learning (ICML). 2019. pp. 1351–1360.
Deligiannidis G, Bouchard-Côté A, Doucet A. Exponential Ergodicity of the Bouncy Particle Sampler. Annals of Statistics. 2019; 47: 1268–1287.
Dinsdale DR, Salibian-Barrera M. Modelling ocean temperatures from bio-probes under preferential sampling. Annals of Applied Statistics [Internet]. 2019; 13(2): 713-745. DOI: 10.1214/18-AOAS1217 URL: https://arxiv.org/abs/1901.02630 Software: https://github.com/msalibian/PreferentialMovement
Dinsdale DR, Salibian-Barrera M. Methods for preferential sampling in geostatistics. Journal of the Royal Statistical Society Series C [Internet]. 2019; 68(1): 198. DOI: 10.1111/rssc.12286 URL: https://dx.doi.org/10.1111/rssc.12286 Software: https://github.com/msalibian/PreferentialSampling
Fernandez-Fontelo A, Cabana A, Joe H, Puig P, Morina D. Untangling serially dependent underreported count data for gender-based violence. Statistics in Medicine. 2019; 38: 4404-4422. DOI: 10.1002/sim.8306, Early Access Date = JUL 2019
Fu E, Heckman N. Model-based curve registration via stochastic approximation EM algorithm. Computational Statistics and Data Analysis [Internet]. 2019; 131. URL: https://arxiv.org/abs/1712.07265
Hadley D, Joe H, Nolde N. On the selection of loss severity distributions to model operational risk. Journal of Operational Risk. 2019; 14: 73-94. DOI: 10.21314/JOP.2019.229
Högg T, Zhao Y, Gustafson P, Petkau J, Fisk J, Marrie RA, et al.. Adjusting for differential misclassification in matched case-control studies utilizing health administrative data. Statistics in Medicine. 2019; 38: 3669-3681.
Joe H, Li H. Tail densities of skew-elliptical distributions. Journal of Multivariate Analysis. 2019; 171: 421-435. DOI: 10.1016/j.jmva.2019.01.009
Jun S-H, Wong SWK, Zidek JV, Bouchard-Côté A. Sequential decision model for inference and prediction on non-uniform hypergraphs with application to knot matching from computational forestry. Annals of Applied Statistics. 2019; 13: 1678–1707.
Jun S-H, Wong SWK, Zidek JV, Bourchard-Cote A. Sequential decision model for inference and prediction on non-uniform hypergraphs with application to knot matching from computational forestry. Annals of Applied Statistics. 2019; 13: 1678-1707 .
Karim ME, Petkau J, Gustafson P, Platt RW. Comparison of statistical approaches dealing with time-dependent confounding in drug effectiveness studies. Statistical Methods in Medical Research. 2019; 28: 323-324 .
Khodadadi A, McDonald DJ. Algorithms for Estimating Trends in Global Temperature Volatility. In: Hentenryck PV, Zhou Z-H. Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19) [Internet]. Association for the Advancement of Artificial Intelligence; 2019. URL: https://doi.org/10.1609/aaai.v33i01.3301614
Kingwell E, Leray E, Zhu F, Petkau J, Edan G, Oger J, et al. Multiple sclerosis: Effect of beta-interferon treatment on survival. Brain. 2019; 142: 1324-1333.

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