| Introduction to functional data analysis P Kokoszka, M Reimherr Chapman and Hall/CRC, 2017 | 648 | 2017 |
| Break detection in the covariance structure of multivariate time series models A Aue, S Hörmann, L Horváth, M Reimherr Annals of Statistics 37 (6B), 4046-4087, 2009 | 470 | 2009 |
| Determining the order of the functional autoregressive model P Kokoszka, M Reimherr Journal of Time Series Analysis 34 (1), 116-129, 2013 | 109 | 2013 |
| Child weight gain trajectories linked to oral microbiota composition SJC Craig, D Blankenberg, ACL Parodi, IM Paul, LL Birch, JS Savage, ... Scientific reports 8 (1), 14030, 2018 | 76 | 2018 |
| The function-on-scalar LASSO with applications to longitudinal GWAS RF Barber, M Reimherr, T Schill Electronic Journal of Statistics 11 (1), 1351-1389, 2017 | 66 | 2017 |
| Asymptotic normality of the principal components of functional time series P Kokoszka, M Reimherr Stochastic Processes and their Applications 123 (5), 1546-1562, 2013 | 62 | 2013 |
| Testing separability of space-time functional processes P Constantinou, P Kokoszka, M Reimherr Biometrika 104 (2), 425-437, 2017 | 61 | 2017 |
| Delay times of sequential procedures for multiple time series regression models A Aue, L Horváth, ML Reimherr Journal of Econometrics 149 (2), 174-190, 2009 | 61 | 2009 |
| Detection of change in the spatiotemporal mean function O Gromenko, P Kokoszka, M Reimherr Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2017 | 60 | 2017 |
| Types of adult attention-deficit/hyperactivity disorder: a replication analysis FW Reimherr, M Roesler, BK Marchant, TE Gift, W Retz, ... The Journal of Clinical Psychiatry 81 (2), 21798, 2020 | 59 | 2020 |
| Feature screening for time-varying coefficient models with ultrahigh dimensional longitudinal data W Chu, R Li, M Reimherr The annals of applied statistics 10 (2), 596, 2016 | 59 | 2016 |
| A functional data analysis approach for genetic association studies M Reimherr, D Nicolae | 49 | 2014 |
| Two sample inference in functional linear models L Horváth, P Kokoszka, M Reimherr Canadian Journal of Statistics 37 (4), 571-591, 2009 | 49 | 2009 |
| High-dimensional adaptive function-on-scalar regression Z Fan, M Reimherr Econometrics and statistics 1, 167-183, 2017 | 48 | 2017 |
| On quantifying dependence: A framework for developing interpretable measures M Reimherr, DL Nicolae | 47 | 2013 |
| A geometric approach to confidence regions and bands for functional parameters H Choi, M Reimherr Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2018 | 46 | 2018 |
| Prior sample size extensions for assessing prior impact and prior-likelihood discordance M Reimherr, XL Meng, DL Nicolae Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2021 | 41* | 2021 |
| Nonlinear functional modeling using neural networks AR Rao, M Reimherr Journal of Computational and Graphical Statistics 32 (4), 1248-1257, 2023 | 37 | 2023 |
| Coherent synthesis of genomic associations with phenotypes and home environments JR Lasky, BR Forester, M Reimherr Molecular Ecology Resources 18 (1), 91-106, 2018 | 37 | 2018 |
| Benefits and pitfalls of the exponential mechanism with applications to hilbert spaces and functional pca J Awan, A Kenney, M Reimherr, A Slavković International Conference on Machine Learning, 374-384, 2019 | 36 | 2019 |
