| Quantifying alternative splicing from paired-end RNA-sequencing data D Rossell, CSO Attolini, M Kroiss, A Stöcker The annals of applied statistics 8 (1), 309, 2014 | 52 | 2014 |
| The effect of rapid relative humidity changes on fast filter-based aerosol-particle light-absorption measurements: uncertainties and correction schemes S Düsing, B Wehner, T Müller, A Stöcker, A Wiedensohler Atmospheric Measurement Techniques 12 (11), 5879-5895, 2019 | 19 | 2019 |
| Multivariate functional additive mixed models A Volkmann, A Stöcker, F Scheipl, S Greven Statistical Modelling 23 (4), 303-326, 2023 | 16 | 2023 |
| Elastic analysis of irregularly or sparsely sampled curves L Steyer, A Stöcker, S Greven Biometrics 79 (3), 2103-2115, 2023 | 13 | 2023 |
| Pedestrian exposure to black carbon and PM2.5 emissions in urban hot spots: new findings using mobile measurement techniques and flexible Bayesian … HD Alas, A Stöcker, N Umlauf, O Senaweera, S Pfeifer, S Greven, ... Journal of exposure science & environmental epidemiology 32 (4), 604-614, 2022 | 11 | 2022 |
| Boosting functional response models for location, scale and shape with an application to bacterial competition A Stöcker, S Brockhaus, SA Schaffer, B Bronk, M Opitz, S Greven Statistical Modelling 21 (5), 385-404, 2021 | 11 | 2021 |
| Functional additive regression on shape and form manifolds of planar curves A Stöcker, S Greven arXiv preprint arXiv:2109.02624, 2021 | 9* | 2021 |
| Additive density-on-scalar regression in Bayes Hilbert spaces with an application to gender economics EM Maier, A Stöcker, B Fitzenberger, S Greven arXiv preprint arXiv:2110.11771, 2021 | 8 | 2021 |
| sparseFLMM: Functional Linear Mixed Models for Irregularly or Sparsely Sampled Data J Cederbaum, A Volkmann, A Stöcker R package version 0.3. 0, URL https://CRAN. R-project. org/package= sparseFLMM, 2019 | 6 | 2019 |
| Elastic full Procrustes analysis of plane curves via Hermitian covariance smoothing A Stöcker, M Pfeuffer, L Steyer, S Greven arXiv preprint arXiv:2203.10522, 2022 | 4 | 2022 |
| Package ‘FDboost’ S Brockhaus, D Ruegamer, A Stoecker, T Hothorn | 3 | 2023 |
| A Bayesian Time-Varying Autoregressive Model for Improved Short-and Long-Term Prediction C Berninger, A Stöcker, D Rügamer arXiv preprint arXiv:2006.05750, 2020 | 2 | 2020 |
| A Bayesian time‐varying autoregressive model for improved short‐term and long‐term prediction C Berninger, A Stöcker, D Rügamer Journal of Forecasting 41 (1), 181-200, 2022 | 1 | 2022 |
| Comments on: shape-based functional data analysis A Stöcker, L Steyer, S Greven TEST, 1-11, 2023 | | 2023 |
| 4. Paper III: Regression in Quotient Metric Spaces with a Focus On Elastic Curves L Steyer, A Stöcker, S Greven Statistical Methods for Sparse Functional Object Data: Elastic Curves …, 2023 | | 2023 |
| Elastic regression for irregularly sampled curves in L Steyer, A Stöcker, S Greven arXiv preprint arXiv:2305.02075, 2023 | | 2023 |
| 5. Paper IV: Functional Additive Models on Manifolds of Planar Shapes and Forms A Stöcker, L Steyer, S Greven Statistical Methods for Sparse Functional Object Data: Elastic Curves …, 2023 | | 2023 |
| Flexible regression for functional object data: curves, shapes and densities A Stöcker lmu, 2022 | | 2022 |
| 3. Paper II: Elastic Full Procrustes Analysis of Plane Curves via Hermitian Covariance Smoothing A Stöcker, M Pfeuffer, L Steyer, S Greven Statistical Methods for Sparse Functional Object Data: Elastic Curves …, 2022 | | 2022 |
| 2. Paper I: Elastic Analysis of Irregularly or Sparsely Sampled Curves L Steyer, A Stöcker, S Greven Statistical Methods for Sparse Functional Object Data: Elastic Curves …, 2022 | | 2022 |
Sonja GrevenChair of Statistics, Humboldt-Universität zu BerlinVerified email at hu-berlin.de
