Research

Research

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  1. Department of Statistics
  2. Research
  3. Publications by Department Members

Publications by Department Members

Submitted

Campbell T, Broderick T. Automated scalable Bayesian inference via Hilbert coresets. arXiv:1710.05053. Submitted;.
Freue GVCohen, Kepplinger D, Salibian-Barrera M, Smucler E. Proteomic biomarker study using novel robust penalized elastic net estimators. Annals of Applied Statistics. Submitted.
Huggins J, Campbell T, Kasprzak M, Broderick T. Scalable Gaussian process inference with finite-data mean and variance guarantees. arXiv:1806.10234. Submitted;.
Watson J, Joy R, Tollit D, Thornton SJ, Auger-Méthé M. A general framework for estimating the spatio-temporal distribution of a species using multiple data types. Submitted.
Watson J. A fast Monte Carlo test for preferential sampling. Submitted.

In Press

Campbell T, Huggins J, How J, Broderick T. Truncated random measures. Bernoulli. In Press;.
Campbell T, Kulis B, How J. Dynamic clustering algorithms via small-variance analysis of Markov chain mixture models. IEEE Transactions on Pattern Analysis and Machine Intelligence. In Press;.
Högg T, Zhao Y, Gustafson P, Petkau J, Fisk J, Marrie RAnn, et al.. Adjusting for differential misclassification in matched case-control studies utilizing health administrative data. Statistics in Medicine. In Press;.
Lennox RJ, Engler-Palma C, Kowarski K, Filous A, Whitlock R, Cooke SJ, et al. Optimizing marine spatial plans with animal tracking data. Canadian Journal of Fisheries and Aquatic Sciences. In Press;.

2021

Boente G, Salibian-Barrera M. Robust functional principal components for sparse longitudinal data. Metron. 2021;. DOI: 10.1007/s40300-020-00193-3 Preprint: https://arxiv.org/abs/2012.01540 Software: https://github.com/msalibian/sparseFPCA
Bouchard-Côté A, Chern K, Cubranic D, Hosseini S, Hume J, Lepur M, et al.. Blang: Probabilitistic Programming for Combinatorial Spaces. Journal of Statistical Software. 2021; (Accepted).
Chen J, Li P, Liu Y, Zidek JV. Composite empirical likelihood for multisample clustered data. Journal of Nonparametric Statistics. Taylor & Francis; 2021; 33: 60–81.
Chen J, Li P, Liu Y, Zidek JV. Permutation tests under a rotating sampling plan with clustered data. Journal of nonparametric statistics. 2021; 33: 60-81.
Chen J, Li P, Qin J, Yu T. Test for homogeneity with unordered paired observations. Electronic Journal of Statistics. Institute of Mathematical Statistics and Bernoulli Society; 2021; 15: 1661–1694.
Chen J, Li P, Liu Y, Zidek JV. Composite empirical likelihood for multisample clustered data. J Nonparametric Statistics. 2021;: Accepted Apr 2021.
Ju X, Salibian-Barrera M. Robust Boosting for Regression Problems. Computational Statistics and Data Science [Internet]. 2021; 153. DOI: 10.1016/j.csda.2020.107065 URL: https://arxiv.org/abs/2002.02054 Software: https://github.com/xmengju/RRBoost
Martínez A, Salibian-Barrera M. RBF: An R package to compute a robust backfitting estimator for additive models. The Journal of Open Source Software. 2021; 6(60). DOI: 10.21105/joss.02992 Software: https://github.com/msalibian/RBF
Pan S, Fan S, Wong S, Zidek JV, Rhodin H. Ellipse Detection and Localization with Application to Knots in Sawn Lumber I. 2021 IEEE Winter Conference on Applications of Computer Vision (WACV). 2021.
Park YP, Kellis M. CoCoA-diff: counterfactual inference for single-cell gene expression analysis. Genome Biol. BioMed Central; 2021; 22: 1–23.
Salehi S, others . Clonal fitness inferred from time-series modelling of single-cell cancer genomes. Nature. 2021; (Accepted).
Syed S, Romaniello V, Campbell T, Bouchard-Côté A. Parallel Tempering on Optimized Paths. In International Conference on Machine Learning (ICML). 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).
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. Density ratio model with data-adaptive basis function. arXiv preprint arXiv:2103.03445. 2021;.
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
Chang B, Joe H. Copula diagnostics for asymmetries and conditional dependence. Journal of Applied Statistics. 2020; 47: 1587-1615. DOI: 10.1080/02664763.2019.1685080, Early Access Date = NOV 2019
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.
Chen J, Liu Y, Taylor C, Zidek J. Permutation tests under a rotating sampling plan with clustered data. arXiv preprint arXiv:2004.13892. 2020;.
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).
He M, Chen J. Consistency of the MLE under a two-parameter gamma mixture model with a structural shape parameter. arXiv preprint arXiv:2011.04058. 2020;.
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, Heckman N. Dimensional Analysis in Statistical Modelling. Statistical Science. 2020;: Submitted.
Lee TYoon, Zidek JV. Scientific versus statistical modelling: a unifying approach. arXiv preprint arXiv:2002.11259. 2020 .
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;: To appear.
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.
Zhang AGong, Zhu G, Chen J. Empirical Likelihood Ratio Test on quantiles under a Density Ratio Model. arXiv preprint arXiv:2007.10586. 2020;.
Zhang Q, Chen J. Distributed Learning of Finite Gaussian Mixtures. arXiv preprint arXiv:2010.10412. 2020;.
Zhang Q, Chen J. A Unified Framework for Gaussian Mixture Reduction with Composite Transportation Distance. arXiv preprint arXiv:2002.08410. 2020;.
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

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

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