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  1. Department of Statistics
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  4. Publications

Publications by Daniel J. McDonald

2024

Vinci-Booher S, McDonald DJ, Berquist E, Pestilli F. Associative white matter tracts selectively predict sensorimotor learning. Communications Biology [Internet]. 2024; 7: 762. URL: https://doi.org/10.1038/s42003-024-06420-1
Mathis SM, Webber AE, León TM, Murray EL, Sun M, White LA, et al.. Evaluation of FluSight influenza forecasting in the 2021-22 and 2022-23 seasons with a new target laboratory-confirmed influenza hospitalizations. Nature Communications [Internet]. 2024; 15: 6289. URL: https://doi.org/10.1038/s41467-024-50601-9
Liu J, Cai Z, Gustafson P, McDonald DJ. rtestim: Time-varying reproduction number estimation with trend filtering. PLOS Computational Biology [Internet]. 2024; 20: e1012324. URL: https://doi.org/10.1371/journal.pcbi.1012324
Liang X, Cohen A, Heinsfeld ASólon, Pestilli F, McDonald DJ. sparsegl: An R Package for Estimating Sparse Group Lasso. Journal of Statistical Software [Internet]. 2024; 110: 1–23. URL: https://doi.org/10.18637/jss.v110.i06
Tuzhilina E, Hastie TJ, McDonald DJ, J. Tay K, Tibshirani R. Smooth multi-period forecasting with application to prediction of COVID-19 cases. Journal of Computational and Graphical Statistics [Internet]. 2024; 33: 955-967. URL: https://doi.org/10.1080/10618600.2023.2285337
Sadhanala V, Bassett R, Sharpnack J, McDonald DJ. Exponential family trend filtering on lattices. Electronic Journal of Statistics [Internet]. 2024; 18: 1749–1814. URL: https://doi.org/10.1214/24-EJS2241

2023

Pham D, Ding L, McDonald DJ, Nebel MBeth, Mejia A. Less is more: Balancing noise reduction and data retention in fMRI with projection scrubbing. Neuroimage [Internet]. 2023; 270: 119972. URL: {https://doi.org/10.1016/j.neuroimage.2023.119972

2022

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
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

2021

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
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
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
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

2020

Homrighausen D, McDonald DJ. Compressed and penalized linear regression. Journal of Computational and Graphical Statistics [Internet]. 2020; 29: 309–322. URL: https://doi.org/10.1080/10618600.2019.1660179
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

2019

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

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

2017

McDonald DJ. Minimax Density Estimation for Growing Dimension [Internet]. Singh A, Zhu J. Proceedings of the Twentieth International Conference on Artificial Intelligence and Statistics (AISTATS). PMLR; 2017. pp. 194–203. URL: http://proceedings.mlr.press/v54/mcdonald17a.html
Ding L, McDonald DJ. Predicting phenotypes from microarrays using amplified, initially marginal, eigenvector regression. Bioinformatics [Internet]. 2017; 33: i350–i358. URL: http://dx.doi.org/10.1093/bioinformatics/btx265
Homrighausen D, McDonald DJ. Risk consistency of cross-validation for lasso-type procedures. Statistica Sinica [Internet]. 2017; 27: 1017–1036. URL: http://dx.doi.org/10.5705/ss.202015.0355
McDonald DJ, Shalizi CRohilla, Schervish M. Nonparametric risk bounds for time-series forecasting. Journal of Machine Learning Research [Internet]. 2017; 18: 1–40. URL: http://www.jmlr.org/papers/v18/13-336.html

2016

Homrighausen D, McDonald DJ. On the Nyström and Column-Sampling Methods for the Approximate Principal Components Analysis of Large Data Sets. Journal of Computational and Graphical Statistics [Internet]. 2016; 25: 344–362. URL: http://dx.doi.org/10.1080/10618600.2014.995799

2015

Loewenstein G, Krishnamurti T, Kopsic J, McDonald DJ. Does Increased Sexual Frequency Enhance Happiness?. Journal of Economic Behavior and Organization [Internet]. 2015; 116: 206–218. URL: http://dx.doi.org/10.1016/j.jebo.2015.04.021
McDonald DJ, Shalizi CRohilla, Schervish M. Estimating beta-mixing coefficients via histograms. Electronic Journal of Statistics [Internet]. 2015; 9: 2855–2883. URL: http://dx.doi.org/10.1214/15-EJS1094

2014

Homrighausen D, McDonald DJ. Leave-one-out cross-validation is risk consistent for lasso. Machine Learning [Internet]. 2014; 97: 65–78. URL: http://dx.doi.org/10.1007/s10994-014-5438-z

2013

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

2012

McDonald DJ. Generalization error bounds for state-space models. Carnegie Mellon University; 2012.
J. Jue JS, Press MJ, McDonald DJ, Volpp KG, Asch DA, Mitra N, et al. The impact of price discounts and calorie messaging on beverage consumption: A multi-site field study. Preventive Medicine [Internet]. 2012; 55: 629–633. URL: http://dx.doi.org/10.1016/j.ypmed.2012.10.009

2011

McDonald DJ, Shalizi CR, Schervish M. Estimating beta-mixing coefficients. In: Gordon G, Dunson D, Dudík M. Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS) [Internet]. PMLR; 2011. pp. 516–524. URL: http://proceedings.mlr.press/v15/mcdonald11a.html

2008

McDonald DJ, Thornton DL. Primer on the Mortgage Market and Mortgage Finance. The Federal Reserve Bank of St. Louis Review [Internet]. 2008; 90: 31–46. URL: https://files.stlouisfed.org/files/htdocs/publications/review/08/01/McDonald.pdf