Research

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Publications by Department Members

2020

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 .
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;: 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.
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, 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
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: Chaudhuri K, Sugiyama M. 22ND International Conference on Artificial Intelligence and Statistics, Vol 89. 2019. pp. 353-361.
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
Chen J, Feng Z. A discussion of ‘prior-based Bayesian information criterion’. Statistical Theory and Related Fields. 2019;: 1–3.
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.
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. 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
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
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.
Krupskii P, Joe H. Nonparametric estimation of multivariate tail probabilities and tail dependence coefficients. Journal of Multivariate Analysis. Canadian Stat Sci Inst; 2019; 172: 147-161. DOI: 10.1016/j.jmva.2019.02.013
Loucks CM, Park K, Walker DS, McEwan AH, Timbers TA, Ardiel EL, et al. EFHC1, implicated in juvenile myoclonic epilepsy, functions at the cilium and synapse to modulate dopamine signaling. Elife. 2019; 8: e37271.
Luo H, Freue GVCohen, Zhao X, Bouchard-Côté A, Burstyn I, Gustafson P. A new perspective on the benefits of the gene-environment independence in case-control studies. The Canadian Journal of Statistics. 2019; 47: 473–486.
Wang L, Wang S, Bouchard-Côté A. An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics. Systematic Biology. 2019; (Accepted).
Wang L, Wang S, Bouchard-Côté A. An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics. Systematic Biology. 2019; 69: 155–183.
Watson J, V. Zidek J, Shaddick G. A general theory for preferential sampling in environmental networks. Annals of Applied Statistics. 2019;: 2662-2700.
Watson J, Zidek JV, Shaddick G. A General Theory for Preferential Sampling in Environmental Networks. Annals of Applied Statistics. 2019;: Accepted.
Wong SWK, Zidek JV. The duration of load effect in lumber as stochastic degradation. IEEE Transactions on Reliability. 2019;: 410-419.
Yang C-H, Zidek JV, Wong SWK. Bayesian analysis of accumulated damage models in lumber reliability. Technometrics. 2019; 61: 1-14.
Zhuang WW, Hu B, Chen J. Semiparametric inference for the dominance index under the density ratio model. Biometrika. 2019; 106: 229–241.
Zolaktaf S, Dannenberg F, Winfree E, Bouchard-Côté A, Schmidt M, Condon A. Efficient Parameter Estimation for DNA Kinetics Modeled as Continuous-Time Markov Chains. In The 25th International Conference on DNA Computing and Molecular Programming. 2019. pp. 80–99.

2018

Ardiel EL, McDiarmid TA, Timbers TA, Lee KCY, Safaei J, Pelech SL, et al. Insights into the roles of CMK-1 and OGT-1 in interstimulus interval-dependent habituation in Caenorhabditis elegans. Proceedings of the Royal Society B. 2018; 285: 20182084.
Bierkens J, Bouchard-Côté A, Doucet A, Duncan AB, Fearnhead P, Lienart T, et al.. Piecewise Deterministic Markov Processes for Scalable Monte Carlo on Restricted Domains. Statistics and Probability Letters. 2018; 136: 148–154.

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