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;.

2024

Subedi S, Sumida TS, Park YP. A highly scalable approach to topic modelling in single-cell data by approximate pseudobulk projection. bioRxiv. 2024. p. 2024.02.21.581497.

2023

Chen J. Statistical inference under mixture models. Springer-ICSA. 2023.
Fan S, Wong SW;K, Zidek JV. Knots and their effect on the tensile strength of lumber. Journal of Quality Technology. 2023. pp. 1-13.
Hou L, Xiong X, Park Y, Boix C, James B, Sun N, et al. Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease. Nat. Genet. nature.com; 2023; 55: 1665–1676.
Lee TYoon, Zidek JV, Heckman N. Nondimensionalizing physical and statistical models: a unified approach. Statistical Science. 2023. p. Submitted.
Shaddick G, Zidek JV, Schmidt AM. Spatio–Temporal Methods in Environmental Epidemiology with R. CRC Press; 2023.
Subedi S, Park YP. Single-cell pair-wise relationships untangled by composite embedding model. iScience. 2023; 26: 106025.
Sun N, Victor MB, Park YP, Xiong X, Scannail ANi, Leary N, et al. Human microglial state dynamics in Alzheimer's disease progression. Cell. 2023; 186: 4386–4403.e29.
Sun N, Akay LAnne, Murdock MH, Park Y, Galiana-Melendez F, Bubnys A, et al. Single-nucleus multiregion transcriptomic analysis of brain vasculature in Alzheimer's disease. Nat. Neurosci. 2023; 26: 970–982.
Xiong X, James BT, Boix CA, Park YP, Galani K, Victor MB, et al. Epigenomic dissection of Alzheimer's disease pinpoints causal variants and reveals epigenome erosion. Cell. 2023; 186: 4422–4437.e21.
Zhang Y, Khalilitousi M(sam), Park YP. Unraveling dynamically encoded latent transcriptomic patterns in pancreatic cancer cells by topic modeling. Cell Genomics. 2023; 3: 100388.
Zhang Q, Zhang AGong, Chen J. Gaussian mixture reduction with composite transportation divergence. IEEE Transactions on Information Theory. 2023;. DOI: doi.org/10.1109/TIT.2023.3323346

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
Chen J, Liu Y, Taylor CG, Zidek JV. Permutation tests under a rotating sampling plan with clustered data. The Annals of Applied Statistics. 2022; 16: 936–958.
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
Dean CB, El-Shaarawi AH, Esterby SR, Flemming JMills, Routledge RD, Taylor SW, et al. Canadian contributions to environmetrics. Canadian Journal of Statistics [Internet]. 2022; n/a. DOI: https://doi.org/10.1002/cjs.11743 URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/cjs.11743
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
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
Zhang AGong, Chen Jand. Density ratio model with data-adaptive basis function. Journal of Multivariate Analysis. 2022; 191.
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

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, 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, 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
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
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 applications to knots in sawn lumber images. 2021 IEEE Winter Conference on Applications of Computer Vision (WACV). 2021. pp. 3892-3901.
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).

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