Research

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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.

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;.

2022

Chen J, Liu Y, Taylor CG, Zidek JV. Permutation tests under a rotating sampling plan with clustered data. Ann. Appl. Statist. 2022; 16: 936-958. DOI: 10.1214/21-AOAS1526
Cramer EY, Ray EL, Lopez VK, Bracher J, Brennen A, Rivadeneira AJCastro, et al. Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States. Proceedings of the National Academy of Sciences [Internet]. 2022; 119: e2113561119. URL: https://www.pnas.org/doi/abs/10.1073/pnas.2113561119
Ding L, Zentner GE, McDonald DJ. Sufficient principal component regression for genomics. Bioinformatics Advances [Internet]. 2022; 2: vbac033. URL: https://doi.org/10.1093/bioadv/vbac033
Fan S, Wong SW;K, Zidek JV. Knots and their effect on the tensile strength of lumber. Journal of Quality Technology. 2022. p. Submitted.
He M, Chen J. Consistency of the MLE under two-parameter mixture models with a structural scale parameter. Advances in Data Analysis and Classification [Internet]. 2022; 16: 125-154. URL: http://doi.org/10.1007/s11634-021-00472-5
Lee TYoon, Zidek JV, Heckman N. Nondimensionalizing physical and statistical models: a unified approach. Statistical Science. 2022. p. Submitted.
Zhang Q, Chen J. Distributed learning of finite Gaussian mixtures. Journal of Machine Learning Research [Internet]. 2022; 23: 1-40. URL: \urlhttp://jmlr.org/papers/v23/21-0093.html
Zhang AGong, Chen Jand. Density ratio model with data-adaptive basis function. Journal of Multivariate Analysis. 2022; 191.

2021

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, 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.
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, Yukun L, Zidek J. Monitoring test under nonparametric random effects model. Journal of Nonparametric Statistics [Internet]. 2021; 33: 60-81. URL: https://doi.org/10.1080/10485252.2021.1914337
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
McDonald DJ, Bien J, Green A, Hu AJ, DeFries N, Hyun S, et al. Can Auxiliary Indicators Improve COVID-19 Forecasting and Hotspot Prediction?. Proceedings of the National Academy of Sciences [Internet]. 2021; 118: e2111453118. URL: https://doi.org/10.1073/pnas.2111453118
McDonald DJ, McBride M, Gu Y, Raphael C. Markov-switching State Space Models for Uncovering Musical Interpretation. Annals of Applied Statistics [Internet]. 2021; 15: 1147–1170. URL: https://doi.org/10.1214/21-AOAS1457
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.
Policastro RA, McDonald DJ, Brendel VP, Zentner GE. Flexible analysis of TSS mapping data and detection of TSS shifts with TSRexploreR. NAR Genomics and Bioinformatics [Internet]. 2021; 3: 1–10. URL: https://doi.org/10.1093/nargab/lqab051
Reinhart A, Brooks L, Jahja M, Rumack A, Tang J, Saeed WAl, et al. An Open Repository of Real-Time COVID-19 Indicators. Proceedings of the National Academy of Sciences [Internet]. 2021; 118: e2111452118. URL: https://doi.org/10.1073/pnas.2111452118
Sidrow E, Heckman N, Fortune SME, Trites A, Murphy I, Auger-Méthé M. Modelling multi-scale, state-switching functional data with hidden Markov models. Canadian Journal of Statistics. 2021; 50(1).
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. 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

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