| Statistics and Data Analysis for Financial Engineering: with R examples D Ruppert, DS Matteson Springer, 2015 | 727* | 2015 |
| A nonparametric approach for multiple change point analysis of multivariate data DS Matteson, NA James Journal of the American Statistical Association 109 (505), 334-345, 2014 | 621 | 2014 |
| ecp: An R package for nonparametric multiple change point analysis of multivariate data NA James, DS Matteson Journal of Statistical Software 62 (7), 1-25, 2014 | 310 | 2014 |
| VARX-L: Structured regularization for large vector autoregressions with exogenous variables WB Nicholson, DS Matteson, J Bien International Journal of Forecasting 33 (3), 627-651, 2017 | 227* | 2017 |
| Independent component analysis via distance covariance DS Matteson, RS Tsay Journal of the American Statistical Association 112 (518), 623-637, 2017 | 147 | 2017 |
| Forecasting emergency medical service call arrival rates DS Matteson, MW McLean, DB Woodard, SG Henderson The Annals of Applied Statistics 5 (2B), 1379-1406, 2011 | 144 | 2011 |
| High Dimensional Forecasting via Interpretable Vector Autoregression WB Nicholson, I Wilms, J Bien, DS Matteson J. Mach. Learn. Res. 21, 166:1-166:52, 2020 | 141 | 2020 |
| Travel time estimation for ambulances using Bayesian data augmentation BS Westgate, DB Woodard, DS Matteson, SG Henderson The Annals of Applied Statistics, 1139-1161, 2013 | 140 | 2013 |
| Dynamic orthogonal components for multivariate time series DS Matteson, RS Tsay Journal of the American Statistical Association 106 (496), 1450-1463, 2011 | 98 | 2011 |
| Dynamic shrinkage processes DR Kowal, DS Matteson, D Ruppert Journal of the Royal Statistical Society: Series B 81 (4), 781–804, 2019 | 96 | 2019 |
| A spatio-temporal point process model for ambulance demand Z Zhou, DS Matteson, DB Woodard, SG Henderson, AC Micheas Journal of the American Statistical Association 110 (509), 6-15, 2015 | 84 | 2015 |
| Leveraging cloud data to mitigate user experience from ‘breaking bad’ NA James, A Kejariwal, DS Matteson 2016 IEEE International Conference on Big Data (Big Data), 3499-3508, 2016 | 82 | 2016 |
| Large-network travel time distribution estimation for ambulances BS Westgate, DB Woodard, DS Matteson, SG Henderson European Journal of Operational Research 252 (1), 322-333, 2016 | 82 | 2016 |
| Probabilistic transformer for time series analysis B Tang, DS Matteson Advances in Neural Information Processing Systems 34, 23592-23608, 2021 | 79 | 2021 |
| A Bayesian multivariate functional dynamic linear model DR Kowal, DS Matteson, D Ruppert Journal of the American Statistical Association 112 (518), 733-744, 2017 | 73 | 2017 |
| Disability-inclusive employer practices and hiring of individuals with disabilities WA Erickson, S von Schrader, SM Bruyère, SA VanLooy, DS Matteson Rehabilitation Research, Policy, and Education 28 (4), 309-328, 2014 | 70 | 2014 |
| Predicting ambulance demand: A spatio-temporal kernel approach Z Zhou, DS Matteson Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015 | 67 | 2015 |
| Stationarity of generalized autoregressive moving average models DB Woodard, DS Matteson, SG Henderson Electronic Journal of Statistics 5, 800-828, 2011 | 63* | 2011 |
| BigVAR: Tools for modeling sparse high-dimensional multivariate time series W Nicholson, DS Matteson, J Bien arXiv preprint arXiv:1702.07094, 2017 | 52* | 2017 |
| Functional autoregression for sparsely sampled data DR Kowal, DS Matteson, D Ruppert Journal of Business & Economic Statistics 37 (1), 97-109, 2019 | 51 | 2019 |
