Research

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Publications by Department Members

2014

Hua L, Joe H, Li H. Relations between hidden regular variation and the tail order of copulas. Journal of Applied Probability. Applied Probability Trust; 2014; 51: 37-57. DOI: 10.1017/S0021900200010068
Hua L, Joe H. Strength of tail dependence based on conditional tail expectation. Journal of Multivariate Analysis. Elsevier Inc; 2014; 123: 143-159. DOI: 10.1016/j.jmva.2013.09.001
Joe H. Dependence Modeling with Copulas [Internet]. Boca Raton, FL: Chapman & Hall/CRC; 2014. URL: http://www.crcpress.com/product/isbn/9781466583221
Jun S-H, Bouchard-Côté A. Memory (and time) efficient sequential Monte Carlo. In International Conference on Machine Learning (ICML). 2014. pp. 514–522.
Karim MEhsanul, Gustafson P, Petkau J, Zhao Y, Shirani A, Kingwell E, et al. Marginal Structural Cox Models for Estimating the Association Between β-Interferon Exposure and Disease Progression in a Multiple Sclerosis Cohort. American journal of epidemiology. Oxford University Press; 2014; 180: 160–171. DOI: 10.1093/aje/kwu125
Karim ME, Gustafson P, Petkau J, Zhao Y, Shirani A, Kingwell E, et al. Marginal structural Cox models for estimating the association between beta-interferon exposure and disease progression in a multiple sclerosis cohort. American Journal of Epidemiology. JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA: OXFORD UNIV PRESS INC; 2014; 180: 160-171. DOI: 10.1093/aje/kwu125
Koulis T, Muthukumarana S, Briercliffe C. A Bayesian stochastic model for batting performance evaluation in one-day cricket. Journal of Quantitative Analysis in Sports [Internet]. 2014; 10: 1–13. DOI: 10.1515/jqas-2013-0057 URL: http://www.degruyter.com/view/j/jqas.2014.10.issue-1/jqas-2013-0057/jqas-2013-0057.xml
Le N, Leung A, Brooks-Wilson A, Cook L, Swenerton K, Demers P, et al. Occupational exposure and ovarian cancer risk. Cancer causes Control. Cancer causes Control. 2014; 7: 829-841.
Levinson DF, Mostafavi S, Milaneschi Y, Rivera M, Ripke S, Wray NR, et al. Genetic Studies of Major Depressive Disorder: Why Are There No Genome-wide Association Study Findings and What Can We Do About It?. BIOLOGICAL PSYCHIATRY. 360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA: ELSEVIER SCIENCE INC; 2014; 76: 510-512. DOI: 10.1016/j.biopsych.2014.07.029
Li S, Chen J, Guo J, Jing B-Y, Tsang S-Y, Xue H. Likelihood Ratio Test for Multi-Sample Mixture Model and its Application to Genetic Imprinting. Journal of the American Statistical Association. Taylor & Francis; 2014;: 00–00.
Lindsten F, Johansen AM, Naesseth CA, Kirkpatrick B, Schon TB, Aston J, et al. Divide-and-Conquer with Sequential Monte Carlo. arXiv. 2014; 1406.4993.
Lindsten F, Johansen AM, Naesseth CA, Kirkpatrick B, Schon TB, Aston J, et al. Divide-and-Conquer with Sequential Monte Carlo. arXiv. 2014; 1406.4993.
Liu Y, Battaile BC, Zidek JV, Trites AW. Bayesian melding of the dead-reckoned path and GPS measurements for an accurate and high-resolution path of marine mammals. arXiv preprint arXiv:1411.6683. 2014.
Liu Y, Battaile BC, Zidek JV, Trites AW. Bayesian Melding of the Dead-Reckoned path and GPS measurements for an accurate and high-resolution path of marine mammals. arXiv preprint arXiv: 1411.6683. 2014;.
Liu Y, Chen J, Li T. Level-specific correction for nonparametric likelihoods. Journal of Nonparametric Statistics. Taylor & Francis; 2014; 26: 433–449.
Lublin FD, Reingold SC, Cohen JA, Cutter GR, Soelberg-Sorensen P, Thompson AJ, et al. Defining the clinical course of multiple sclerosis: The 2013 revisions. Neurology. TWO COMMERCE SQ, 2001 MARKET ST, PHILADELPHIA, PA 19103 USA: LIPPINCOTT WILLIAMS & WILKINS; 2014; 83: 278-286.
Maydeu-Olivares A, Joe H. Assessing approximate fit in categorical data analysis. Multivariate Behavioral Research. Routledge Journals, Taylor & Francis Ltd; 2014; 49: 305-328. DOI: 10.1080/00273171.2014.911075
Mostafavi S, Battle A, Zhu X, Potash JB, Weissman MM, Shi J, et al. Type I interferon signaling genes in recurrent major depression: increased expression detected by whole-blood RNA sequencing. Molecular psychiatry. Nature Publishing Group; 2014; 19: 1267–1274.
Mostafavi S, Ortiz-Lopez A, Bogue MA, Hattori K, Pop C, Koller D, et al. Variation and Genetic Control of Gene Expression in Primary Immunocytes across Inbred Mouse Strains. JOURNAL OF IMMUNOLOGY. 9650 ROCKVILLE PIKE, BETHESDA, MD 20814 USA: AMER ASSOC IMMUNOLOGISTS; 2014; 193: 4485-4496. DOI: 10.4049/jimmunol.1401280
Ng CT, Joe H. Model comparison with composite likelihood information criteria. Bernoulli. Int Statistical Inst; 2014; 20: 1738-1764. DOI: 10.3150/13-BEJ539
Nolde N. The effect of aggregation on extremes from asymptotically independent light-tailed risks. EXTREMES. 233 SPRING ST, NEW YORK, NY 10013 USA: SPRINGER; 2014; 17: 615-631. DOI: 10.1007/s10687-014-0192-y
Nolde N, Parker G. Stochastic analysis of life insurance surplus. INSURANCE MATHEMATICS & ECONOMICS. PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS: ELSEVIER SCIENCE BV; 2014; 56: 1-13. DOI: 10.1016/j.insmatheco.2014.02.006
Nolde N. Geometric interpretation of the residual dependence coefficient. JOURNAL OF MULTIVARIATE ANALYSIS. 525 B STREET, STE 1900, SAN DIEGO, CA 92101-4495 USA: ELSEVIER INC; 2014; 123: 85-95. DOI: 10.1016/j.jmva.2013.08.018
Norman WV, Brooks M, Brant R, Soon JA, Majdzadeh A, Kaczorowski J. What proportion of Canadian women will accept an intrauterine contraceptive at the time of second trimester abortion? Baseline data from a randomized controlled trial. J Obstet Gynaecol Can. 2014; 36: 51–59.
Raj T, Rothamel K, Mostafavi S, Ye C, Lee MN, Replogle JM, et al. Polarization of the Effects of Autoimmune and Neurodegenerative Risk Alleles in Leukocytes. SCIENCE. 1200 NEW YORK AVE, NW, WASHINGTON, DC 20005 USA: AMER ASSOC ADVANCEMENT SCIENCE; 2014; 344: 519-523. DOI: 10.1126/science.1249547
Reich DS, White R, Cortese ICM, Vuolo L, Shea CD, Collins TL, et al. Sample-size calculations for short-term proof-of-concept studies of tissue protection and repair in MS lesions via conventional clinical imaging. In MULTIPLE SCLEROSIS JOURNAL. SAGE PUBLICATIONS LTD 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND; 2014. pp. 284–284.
Roth A, Khattra J, Yap D, Wan A, Laks E, Biele J, et al. PyClone: statistical inference of clonal population structure in cancer. Nature Methods. 2014; 11: 396–398.
Shaddick G, Zidek JV. A case study in preferential sampling: Long term monitoring of air pollution in the UK. Spatial Statistics. Elsevier; 2014; 9: 51–65.
Shahriari B, Wang Z, Hoffman MW, Bouchard-Côté A, de Freitas N. An Entropy Search Portfolio for Bayesian Optimization. arXiv. 2014; 1406.4625.
Shahriari B, Wang Z, Hoffman MW, Bouchard-Côté A, de Freitas N. An Entropy Search Portfolio for Bayesian Optimization. arXiv. 2014; 1406.4625.
Sharma AA, Jen R, Brant R, Ladd M, Huang Q, Skoll A, et al. Hierarchical maturation of innate immune defences in very preterm neonates. Neonatology. 2014; 106: 1–9.
Shi T, Steyn D, Welch WJ. Air Quality Model Evaluation Using Gaussian Process Modelling and Empirical Orthogonal Function Decomposition. In Air Pollution Modeling and its Application XXIII [Internet]. Springer International Publishing; 2014. pp. 457–462. URL: http://link.springer.com/chapter/10.1007/978-3-319-04379-1_75
Shirani A, Zhao Y, Karim ME, Petkau J, Gustafson P, Evans C, et al. Investigation of heterogeneity in the association between interferon beta and disability progression in multiple sclerosis: an observational study. European Journal of Neurology. Wiley Online Library; 2014; 21: 835–844. DOI: 10.1111/ene.12324
Vinall J, Miller SP, Bjornson BH, Fitzpatrick KP, Poskitt KJ, Brant R, et al. Invasive procedures in preterm children: brain and cognitive development at school age. Pediatrics. 2014; 133: 412–421.
Wang D, Gustafson P. On the Impact of Misclassification in an Ordinal Exposure Variable. Epidemiologic Methods. 2014; 3: 97–106. DOI: 10.1515/em-2013-0017
Xia M, Gustafson P. Bayesian sensitivity analyses for hidden sub-populations in weighted sampling. Canadian Journal of Statistics. Wiley Online Library; 2014; 42: 436–450. DOI: 10.1002/cjs.11220
Xu C, Chen J. The Sparse MLE for Ultrahigh-Dimensional Feature Screening. Journal of the American Statistical Association. Taylor & Francis; 2014; 109: 1257–1269.
Zhang J, Heckman N, Cubranic D, Kingsolver JG, Gaydos T, Marron JS. Prinsimp. The R Journal [Internet]. 2014; 6(2): 27–42. URL: http://journal.r-project.org/archive/2014-2/zhang-etal.pdf
Zhang J, Heckman N, Cubranic D, Kingsolver JG, Gaydos T, Marron JS. Prinsimp. R JOURNAL. WIRTSCHAFTSUNIVERSITAT, INST STATISTICS & MATHEMATICS, AUGASSE 2-6, WIEN, 1090, AUSTRIA: R FOUNDATION STATISTICAL COMPUTING; 2014; 6: 27-42.
Zhang H, Zamar RH. Least angle regression for model selection. Wiley Interdisciplinary Reviews: Computational Statistics. Wiley Online Library; 2014; 6: 116–123.
Zhao Y, Li DKB, Petkau AJ, Riddehough A, Traboulsee A. Detection of unusual increases in MRI lesion counts in individual multiple sclerosis patients. Journal of the American Statistical Association [Internet]. 2014; 109: 119–132. DOI: 10.1080/01621459.2013.847373 URL: http://amstat.tandfonline.com/doi/abs/10.1080/01621459.2013.847373
Zidek JV, Shaddick G, Taylor CG, others . Reducing estimation bias in adaptively changing monitoring networks with preferential site selection. The Annals of Applied Statistics. Institute of Mathematical Statistics; 2014; 8: 1640–1670.
Zidek JV, Shaddick G, Taylor CG. Reducing estimation bias in adaptively changing monitoring networks with preferential site selection. The Annals of Applied Statistics. Institute of Mathematical Statistics; 2014; 8: 1640–1670.

2013

Amankwah EK, Friedenreich CM, Magliocco AM, Brant R, Speidel T, Rahman W, et al. Hormonal and reproductive risk factors for sporadic microsatellite stable and unstable endometrial tumors. Cancer Epidemiol. Biomarkers Prev. 2013; 22: 1325–1331.
Amankwah EK, Friedenreich CM, Magliocco AM, Brant R, Courneya KS, Speidel T, et al. Anthropometric measures and the risk of endometrial cancer, overall and by tumor microsatellite status and histological subtype. Am. J. Epidemiol. 2013; 177: 1378–1387.
Ascherio A, Munger K, White R, Kochert K, Simon C, Polman C, et al. Vitamin D as a predictor of multiple sclerosis activity and progression. 2013;.
Ascherio A, Munger KL, White R, others . Supplementary Online Content. 2013;.

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