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Research

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

Publications by Department Members

2013

Balkema G, Embrechts P, Nolde N. The shape of asymptotic dependence. In Prokhorov and Contemporary Probability Theory. Springer; 2013. pp. 43–67.
Bouchard-Côté A, Jordan MI. Evolutionary inference via the Poisson indel process. Proceedings of the National Academy of Sciences. 2013; 110: 1160–1166.
Bouchard-Côté A. A Note on Probabilistic Models over Strings: Inference and Representation with Indexed Matrices. arXiv. 2013; 1301.5054.
Bouchard-Côté A, Hall D, Griffiths TL, Klein D. Automated reconstruction of ancient languages using probabilistic models of sound change. Proceedings of the National Academy of Sciences. 2013; 110: 4224–4229.
Bouchard-Côté A. A Note on Probabilistic Models over Strings: Inference and  Representation with Indexed Matrices. arXiv. 2013; 1301.5054.
Bouchard-Côté A. A note on probabilistic models over strings: the linear algebra approach. Bulletin of Mathematical Biology. 2013; 75: 2529–2550.
Burstyn I, de Vocht F, Gustafson P. What do measures of agreement ($ąppa$) tell us about quality of exposure assessment? Theoretical analysis and numerical simulation. BMJ open. British Medical Journal Publishing Group; 2013; 3: e003952. DOI: 10.1136/bmjopen-2013-003952
Cai S, Chen J, Zidek JV. Hypothesis testing in the presence of multiple samples under density ratio models. arXiv preprint arXiv:1309.4740. 2013;.
Cai S, Chen J, Zidek JV. Hypothesis testing in the presence of multiple samples under density ratio models. Statistica Sinica. 2013;: To appear.
Campbell T, Johnson L, How JP. Multiagent allocation of Markov decision process tasks. In American Control Conference. 2013.
Campbell T, Liu M, Kulis B, How JP, Carin L. Dynamic clustering via asymptotics of the dependent Dirichlet process mixture. In Advances in Neural Information Processing Systems. 2013.
Chau V, Synnes A, Grunau RE, Poskitt KJ, Brant R, Miller SP. Abnormal brain maturation in preterm neonates associated with adverse developmental outcomes. Neurology. 2013; 81: 2082–2089.
Chen J, Huang Y. Finite-sample properties of the adjusted empirical likelihood. Journal of Nonparametric Statistics. Taylor & Francis; 2013; 25: 147–159.
Chen J, Liu Y. Quantile and quantile-function estimations under density ratio model. The Annals of Statistics. Institute of Mathematical Statistics; 2013; 41: 1669–1692.
Chen J. A partial order on uncertainty and information. Journal of Theoretical Probability. Springer US; 2013; 26: 349–359.
Chen J, Li P. MixtureInf-package. Inference for Finite Mixture Models. 2013. p. 2.
Christmann A, Salibian-Barrera M, Van Aelst S. Qualitative Robustness of Bootstrap Approximations for Kernel Based Methods. In: Becker C, Fried R, Kuhnt S. Robustness and Complex Data Structures: Festschrift in Honour of Ursula Gather [Internet]. Berlin, Heidelberg: Springer Berlin Heidelberg; 2013. pp. 263–278. DOI: 10.1007/978-3-642-35494-6_16 URL: http://dx.doi.org/10.1007/978-3-642-35494-6_16
Croux C, Ronchetti E, Salibian-Barrera M, Van Aelst S. Special issue on robust analysis of complex data. COMPUTATIONAL STATISTICS & DATA ANALYSIS. PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS: ELSEVIER SCIENCE BV; 2013; 65: 1-3. DOI: 10.1016/j.csda.2013.04.007
Dimitropoulos A, McQuillen PS, Sethi V, Moosa A, Chau V, Xu D, et al. Brain injury and development in newborns with critical congenital heart disease. Neurology. 2013; 81: 241–248.
Falasinnu T, Gustafson P, Gilbert M, Shoveller J. Risk prediction in sexual health contexts: Protocol. JMIR research protocols. JMIR Publications Inc.; 2013; 2. DOI: 10.2196/resprot.2971
Freue GVCohen, Ortiz-Molina H, Zamar RH. A natural robustification of the ordinary instrumental variables estimator. Biometrics. Wiley Online Library; 2013; 69: 641–650.
Freue GVCohen, Ortiz-Molina H, Zamar RH. A Natural Robustification of the Ordinary Instrumental Variables Estimator. BIOMETRICS. 111 RIVER ST, HOBOKEN 07030-5774, NJ USA: WILEY-BLACKWELL; 2013; 69: 641-650. DOI: 10.1111/biom.12043
Freue GVCohen, Meredith A, Smith D, Bergman A, Sasaki M, Lam KKY, et al. Computational biomarker pipeline from discovery to clinical implementation: plasma proteomic biomarkers for cardiac transplantation. PLoS Comput Biol. Public Library of Science; 2013; 9: e1002963.
Gano D, Chau V, Poskitt KJ, Hill A, Roland E, Brant R, et al. Evolution of pattern of injury and quantitative MRI on days 1 and 3 in term newborns with hypoxic-ischemic encephalopathy. Pediatr. Res. 2013; 74: 82–87.
Gaydos TL, Heckman NE, Kirkpatrick M, Stinchcombe JR, Schmitt J, Kingsolver J, et al. VISUALIZING GENETIC CONSTRAINTS. ANNALS OF APPLIED STATISTICS. 3163 SOMERSET DR, CLEVELAND, OH 44122 USA: INST MATHEMATICAL STATISTICS; 2013; 7: 860-882. DOI: 10.1214/12-AOAS603
Gover A, Chau V, Miller SP, Brant R, McFadden DE, Poskitt KJ, et al. Prenatal and postnatal inflammation in relation to cortisol levels in preterm infants at 18 months corrected age. J Perinatol. 2013; 33: 647–651.
Grunau RE, Cepeda IL, Chau CM, Brummelte S, Weinberg J, Lavoie PM, et al. Neonatal pain-related stress and NFKBIA genotype are associated with altered cortisol levels in preterm boys at school age. PLoS ONE. 2013; 8: e73926.
Gustafson P, Gilbert M, Xia M, Michelow W, Robert W, Trussler T, et al. Impact of Statistical Adjustment for Frequency of Venue Attendance in a Venue-based Survey of Men Who Have Sex With Men. American Journal of Epidemiology. Oxford University Press; 2013; 177: 1157–1164. DOI: 10.1093/aje/kws358
Gustafson P. Bayesian Analysis of Frailty Models. Handbook of Survival Analysis. CRC Press; 2013;: 475.
Hajiaghayi M, Kirkpatrick B, Wang L, Bouchard-Côté A. Efficient Continuous-Time Markov Chain Estimation. arXiv. 2013; 1309.325.
Heckman N, Lockhart R, Nielsen JD. Penalized regression, mixed effects models and appropriate modelling. ELECTRONIC JOURNAL OF STATISTICS. 3163 SOMERSET DR, CLEVELAND, OH 44122 USA: INST MATHEMATICAL STATISTICS; 2013; 7: 1517-1552. DOI: 10.1214/13-EJS809
Hennig C, Liao TF. How to find an appropriate clustering for mixed-type variables with application to socio-economic stratification. Journal of the Royal Statistical Society: Series C (Applied Statistics). Wiley Online Library; 2013; 62: 309–369.
Hollander Z, Chen V, Sidhu K, Lin D, Ng RT, Balshaw R, et al. Predicting acute cardiac rejection from donor heart and pre-transplant recipient blood gene expression. JOURNAL OF HEART AND LUNG TRANSPLANTATION. 360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA: ELSEVIER SCIENCE INC; 2013; 32: 259-265. DOI: 10.1016/j.healun.2012.11.008
Homrighausen D, McDonald DJ. The lasso, persistence, and cross-validation. In: Dasgupta S, McAllester D. Proceedings of the Thirtieth International Conference on Machine Learning (ICML) [Internet]. PMLR; 2013. pp. 1031–1039. URL: http://proceedings.mlr.press/v28/homrighausen13.html
Hsu B-M, Shu M-H, WU LANG. Dynamic performance modelling and measuring for machine tools with continuous-state wear processes. International Journal of Production Research [Internet]. 2013; 51: 4718–4731. DOI: 10.1080/00207543.2013.793858 URL: http://dx.doi.org/10.1080/00207543.2013.793858
Hua L, Joe H. Intermediate tail dependence: a review and some new results. In: Li H, Li X. Stochastic Orders in Reliability and Risk. New York: Springer; 2013. pp. 291-311. DOI: 10.1007/978-1-4614-6892-9_15
Huang MLing, Coia V, Brill P. A Cluster Truncated Pareto Distribution and Its Applications. ISRN Probability and Statistics. 2013; 2013.
Jackson MJ, Gow JL, Evelyn MJ, McMahon TJScott, Campbell H, Sheppard J, et al. Modelling factors that affect the presence of larval mosquitoes (Diptera: Culicidae) in stormwater drainage systems to improve the efficacy of control programmes. The Canadian Entomologist. Cambridge Univ Press; 2013; 145: 674–685.
Jun S-H, Bouchard-Côté A. A Stochastic Map View of Sequential Monte Carlo with Applications to Memory and Network Efficiency. In Randomized Algorithm Workshop at Advances in Neural Information Processing Systems 26 (NIPS). 2013.
Kang J, Brant R, Ghali WA. Statistical methods for the meta-analysis of diagnostic tests must take into account the use of surrogate standards. J Clin Epidemiol. 2013; 66: 566–574.
Kepplinger D, Templ M, Upadhyaya S. Analysis of energy intensity in manufacturing industry using mixed-effects models. Energy [Internet]. 2013; 59: 754 - 763. DOI: http://dx.doi.org/10.1016/j.energy.2013.07.003 URL: http://www.sciencedirect.com/science/article/pii/S0360544213005768
Krupskii P, Joe H. Factor copula models for multivariate data. Journal of Multivariate Analysis. 2013; 120: 85–101.
Krupskii P, Joe H. Factor copula models for multivariate data. Journal of Multivariate Analysis. Elsevier Inc; 2013; 120: 85-101. DOI: 10.1016/j.jmva.2013.05.001
Lin D*, Freue GCohen*, Hollander Z, Mancini GBJohn, Sasaki M, Mui A, et al. Plasma protein biosignatures for detection of cardiac allograft vasculopathy. The Journal of Heart and Lung Transplantation. Elsevier; 2013; 32: 723–733.*Equal contributors.
Lonsdale J, Thomas J, Salvatore M, Phillips R, Lo E, Shad S, et al. The Genotype-Tissue Expression (GTEx) project. NATURE GENETICS. 75 VARICK ST, 9TH FLR, NEW YORK, NY 10013-1917 USA: NATURE PUBLISHING GROUP; 2013; 45: 580-585. DOI: 10.1038/ng.2653
Luo H, Burstyn I, Gustafson P. Investigations of Gene-Disease Associations: Costs and Benefits of Environmental Data. Epidemiology. LWW; 2013; 24: 562–568. DOI: 10.1097/EDE.0b013e3182944dd5
Meyers SM, Vavasour IM, Mädler B, Harris T, Fu E, Li DKB, et al.. Multicenter measurements of myelin water fraction and geometric mean T2: Intra-and intersite reproducibility. Journal of Magnetic Resonance Imaging. Wiley Online Library; 2013; 38: 1445–1453.
Mostafavi S, Battle A, Zhu X, Urban AE, Levinson D, Montgomery SB, et al. Normalizing RNA-Sequencing Data by Modeling Hidden Covariates with Prior Knowledge. PLOS ONE. 1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA: PUBLIC LIBRARY SCIENCE; 2013; 8: e68141. DOI: 10.1371/journal.pone.0068141
Nolde N, Joe H. A Bayesian extreme value analysis of debris flows. WATER RESOURCES RESEARCH. 2000 FLORIDA AVE NW, WASHINGTON, DC 20009 USA: AMER GEOPHYSICAL UNION; 2013; 49: 7009-7022. DOI: 10.1002/wrcr.20494
Nolde N, Joe H. A Bayesian extreme value analysis of debris flows. Water Resources Research. Amer Geophysical Union; 2013; 49: 7009-7022. DOI: 10.1002/wrcr.20494

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