Research

Research

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

Publications by Department Members

2019

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.
Thomas ML, Shaddick G, Simpson D, de Hoogh K, Zidek JV. Data integration for high-resolution, continental-scale estimation of air pollution concentrations. arXiv preprint arXiv:1907.00093. 2019;.
Wang L, Wang S, Bouchard-Côté A. An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics. Systematic Biology. 2019; 69: 155–183.
Wang L, Wang S, Bouchard-Côté A. An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics. Systematic Biology. 2019; (Accepted).
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.
Bouchard-Côté A, Vollmer SJ, Doucet A. The Bouncy Particle Sampler: A non-reversible rejection-free Markov chain Monte Carlo method. Journal of the American Statistical Association. 2018; 113: 855–867.
Cai S, Chen J. Empirical likelihood inference for multiple censored samples. Canadian Journal of Statistics. 2018; 46: 212–232.
Cai S, Chen J. Empirical likelihood inference for multiple censored samples. The Canadian Journal of Statistics. 2018; 46: 232.
Campbell T, Broderick T. Bayesian coreset construction via greedy iterative geodesic ascent. In International Conference on Machine Learning. 2018.
Campbell H, Gustafson P. Conditional equivalence testing: An alternative remedy for publication bias. PloS one. Public Library of Science; 2018; 13: e0195145.
Campbell K, Bouchard-Côté A, Shah S. Probabilistic inference of clonal gene expression through integration of RNA & DNA-seq at single-cell resolution. In HitSeq. 2018.
Campbell H, Gustafson P. The Validity and Efficiency of Hypothesis Testing in Observational Studies with Time-Varying Exposures. Observational Studies [Internet]. 2018;. URL: https://obsstudies.org/validity-efficiency-hypothesis-testing-observational-studies-time-varying-exposures/
Campbell T, Cai D, Broderick T. Exchangeable trait allocations. Electronic Journal of Statistics. 2018; 12: 2290–2322.
Chang B, Meng L, Haber E, Ruthotto L, Begert D, Holtham E. Reversible Architectures for Arbitrarily Deep Residual Neural Networks. In AAAI Conference on Artificial Intelligence. 2018.
Chang B, Zhang Q, Pan S, Meng L. Generating Handwritten Chinese Characters Using CycleGAN. In IEEE Winter Conference on Applications of Computer Vision. 2018.
Chang B, Meng L, Haber E, Tung F, Begert D. Multi-level Residual Networks from Dynamical Systems View. In International Conference on Learning Representations [Internet]. 2018. URL: https://openreview.net/forum?id=SyJS-OgR-
Dinsdale DR, Salibian-Barrera M. Methods for preferential sampling in geostatistics. Journal of the Royal Statistical Society Series C. 2018;. DOI: https://doi.org/10.1111/rssc.12286
Dorri F, Jewell S, Bouchard-Côté A, Shah S. MuClone: somatic mutation detection and classification through probabilistic integration of clonal population information. Communications Biology. 2018; 2: 1–10.
Dorri F, Jewell S, Bouchard-Côté A, Shah S. MuClone: somatic mutation detection and classification through probabilistic integration of clonal population information. Communications Biology . 2018; 2.
Fernandez M, Ban F, Woo G, Hsing M, Yamazaki T, LeBlanc E, et al. Toxic Colors: The Use of Deep Learning for Predicting Toxicity of Compounds Merely from Their Graphic Images. Journal of Chemical Information and Modeling. 2018;(in press).
Gomulkiewicz R, Kingsolver J, Carter P, Heckman N. Variation and evolution of function-valued traits. Annual Review of Ecology, Evolution, and Systematics. 2018; 49(1).
Gustafson P, McCandless LC. When Is a Sensitivity Parameter Exactly That?. Statistical Science. Institute of Mathematical Statistics; 2018; 33: 86–95.
Högg T, Wijnands J, Kingwell E, Zhu F, Lu X, Evans C, et al.. Mining healthcare data for markers of the multiple sclerosis prodrome. Multiple Sclerosis and Related Disorders. 2018;.
Homrighausen D, McDonald DJ. A study on tuning parameter selection for the high-dimensional lasso. Journal of Statistical Computation and Simulation [Internet]. 2018; 88: 2865–2892. URL: http://dx.doi.org/10.1080/00949655.2018.1491575
Joe H. Dependence properties of conditional distributions of some copula models. Methodology and Computing in Applied Probability. 2018; 20: 975-1001. DOI: 10.1007/s11009-017-9544-9 ISSN = 1387-5841
Joe H. Parsimonious graphical dependence models constructed from vines. Canadian Journal of Statistics. 2018; 46: 532-555. DOI: 10.1002/cjs.11481
Karim MEhsanul, Petkau J, Gustafson P, Platt RW, Tremlett H, Group BAMSStudy. Comparison of statistical approaches dealing with time-dependent confounding in drug effectiveness studies. Statistical methods in medical research. SAGE Publications Sage UK: London, England; 2018; 27: 1709–1722.
Karim ME, Petkau J, Gustafson P, Platt RW, Tremlett H, Group BAMSStudy. Comparison of statistical approaches dealing with time-dependent confounding in drug effectiveness studies. Statistical Methods in Medical Research [Internet]. 2018; 27 : 1709-1722. DOI: 10.1177/0962280216668554 URL: http://journals.sagepub.com/doi/abs/10.1177/0962280216668554
Kepplinger D, Smucler E, Freue GVCohen. Improved Robust Estimation of the Residual Scale in High-Dimensional Problems with the Adaptive Elastic Net S-Estimator for Efficient Robust Penalized Linear Regression Methods. In JSM 2018. Vancouver, Canada; 2018.
Kepplinger D, Freue GVCohen. Improving the Robust Estimation of the Residual Scale in High Dimensional Regression Problems with Refitted Cross-Validation using an Elastic Net S-Estimator. In 46th Annual Meeting of the Statistical Society of Canada. Montreal, Canada; 2018.
Kondo Y, Zidek JV, Taylor CG, van Eeden C. Bayesian subset selection procedures with an application to lumber strength properties. Sankhya Ser A. 2018;: Accepted Aug 08, 2018.
Kondo Y, Zidek JV, Taylor CG, van Eeden C. Subset selection procedures with an application to lumber strength properties. Sanhkya Ser B. 2018; 80: 146-172.
Krupskii P, Huser R, Genton M. Factor copula models for replicated spatial data. Journal of the American Statistical Association,. 2018; to appear.
Krupskii P, Joe H, Lee D, Genton M. Extreme value limit of the convolution of exponential and multivariate normal distributions: Link to the Husler- Reiss distribution. Journal of Multivariate Analysis. 2018; 163: 80-95.
Krupskii P, Joe H, Lee D, Genton M. Extreme-value limit of the convolution of exponential and multivariate normal distributions: Link to the Huesler-Reiss distribution. Journal of Multivariate Analysis. 2018; 163: 80-95. DOI: 10.1016/j.jmva.2017.10.006
Krupskii P, Genton M. Linear Factor Copula Models and Their Properties. Scandinavian Journal of Statistics. 2018; to appear.
Lee D, Joe H. Multivariate extreme value copulas with factor and tree dependence structures. Extremes. 2018; 21: 147-176. DOI: 10.1007/s10687-017-0298-0 ISSN = 1386-1999
Lee D, Joe H. Efficient computation of multivariate empirical distribution functions at the observed values. Computational Statistics. 2018; 33: 1413-1428. DOI: 10.1007/s00180-017-0771-x ISSN = 0943-4062
Lee D, Joe H, Krupskii P. Tail-weighted dependence measures with limit being tail dependence coefficient. Journal of Nonparametric Statistics. 2018; to appear.
Lee D, Joe H, Krupskii P. Tail-weighted dependence measures with limit being the tail dependence coefficient. Journal of Nonparametric Statistics. 2018; 30: 262-290. DOI: 10.1080/10485252.2017.1407414
Liu Y, Salibian-Barrera M, Zamar RH, Zidek JV. Using Artificial Censoring to Improve Extreme Tail Quantile Estimates. Journal of the Royal Statistical Society Series C [Internet]. 2018; 67(4): 791-812. DOI: 10.1111/rssc.12262 URL: https://doi.org/10.1111/rssc.12262

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