Philipp Otto

Malinovskaya, A., Mozharovskyi, P. and Otto, P. (2023): Statistical process monitoring of artificial neural networks.,  Technometrics, 66(1), pp. 104-117
DOI: doi.org/10.1080/ 00401706.2023.2239886

Harke, F. H., Merk, M., Otto, P. (2022): Estimation of Asymmetric Spatial Autoregressive Dependence on Irregular Lattices.,  Symmetry 14(7)
DOI: https://doi.org/10.3390/sym14071474

Malinovskaya, A., Mozharovskyi, P., & Otto, P. (2022): Statistical monitoring of models based on artificial intelligence.,  arXiv preprint.
arXiv: 2209.07436

Malinovskaya, A., Otto, P., Peters, T. (2022): Statistical learning for change point and anomaly detection in graphs.,  Artificial Intelligence, Big Data and Data Science in Statistics (pp. 85-109). Springer, Cham.
DOI: doi.org/10.1007/978-3-031-07155-3_4
arXiv: 2011.06080

Otto, P., Schmid, W. (2022): A general framework for spatial GARCH models.,  Stat Papers
DOI: https://doi.org/10.1007/s00362-022-01357-1

Otto, P., Steinert, R. (2022): Estimation of the Spatial Weighting Matrix for Spatiotemporal Data under the Presence of Structural Breaks.,  Journal of Computational and Graphical Statistics
DOI: 10.1080/10618600.2022.2107530

Piter, A., Otto, P., Alkhatib, H. (2022): The Helsinki Bike-Sharing Systems - Insights gained from a spatiotemporal functional model.,  Journal of the Royal Statistical Society Series A
DOI: https://doi.org/10.1111/rssa.12834

Fassò, A., Maranzano, P., & Otto, P. (2021): Spatiotemporal variable selection and air quality impact assessment of COVID-19 lockdown,  Spatial Statistics, 100549.
DOI: https://doi.org/10.1016/j.spasta.2021.100549

Malinovskaya, A., Otto, P. (2021): Online network monitoring,  Statistical Methods & Applications, Special Issue on Network Modelling (online first).
DOI: https://doi.org/10.1007/s10260-021-00589-z

Merk, M., Otto, P. (2021): Directional spatial autoregressive dependence in the conditional first- and second-order moments,  Spatial Statistics (online first)
DOI: https://doi.org/10.1016/j.spasta.2020.100490

Miryam S. Merk, Philipp Otto (2021): Estimation of the spatial weighting matrix for regular lattice data -- An adaptive lasso approach with cross-sectional resampling,  Environmetrics (online first)
DOI: https://doi.org/10.1002/env.2705

Otto, P., Otto, P. (2021): Impact of academic authorship characteristics on article citations,  REVSTAT (online first). Weitere Informationen

Otto, P., Piter, A., Gijsman, R. (2021): Statistical Analysis of Beach Profile Evolution and External Influences: Applying a Spatiotemporal Functional Approach,  Coastal Engineering 170
DOI: https://doi.org/10.1016/j.coastaleng.2021.103999

Antoniuk, A., Merk, M., Otto, P. (2020): Spatial Statistics, or how to extract knowledge from data,  In Handbook of Big Geospatial Data. Springer Handbook Series in Computer Science. Weitere Informationen

Malinovskaya, A., Killick, R., Leeming, K., and Otto, P. (2020): Statistical monitoring of European cross-border physical electricity flows using novel temporal edge network processes.
DOI: doi.org/10.48550/arXiv.2312.16357
arXiv: 2312.16357

Otto, P. (2020): Parallelized Monitoring of Dependent Spatiotemporal Processes,  Frontiers of Statistical Quality Control 13. Weitere Informationen

Robert Garthoff, Philipp Otto (2020): Spatiotemporal procedures for the statistical surveillance of spatial autoregressive models with heavy tails,  Communications in Statistics - Simulation and Computation (online first)
DOI: 10.1080/03610918.2020.1779294

Miryam S. Merk, Philipp Otto (2019): Estimation of Anisotropic, Time‐Varying Spatial Spillovers of Fine Particulate Matter Due to Wind Direction,  Geographical Analysis
DOI: 10.1111/gean.12205

Otto, P., Schmid, W. & Garthoff, R. (2019): Stochastic properties of spatial and spatiotemporal ARCH models,  Statistical Papers, 1-16
DOI: 10.1007/s00362-019-01106-x

Philipp Otto (2019): spGARCH: An R-Package for Spatial and Spatiotemporal ARCH and GARCH models,  The R-Journal Weitere Informationen
DOI: 10.32614/RJ-2019-053

Philipp Otto, Wolfgang Schmid (2018): Discussion of “Statistical methods for network surveillance” by Daniel Jeske, Nathaniel Stevens, Alexander Tartakovsky, and James Wilson,  Applied Stochastic Models in Business and Industry 34(4). pp. 452-456
DOI: 10.1002/asmb.2360

Philipp Otto, Wolfgang Schmid (2018): Spatiotemporal analysis of German real-estate prices,  The Annals of Regional Science Volume 60, Issue 1, pp 41–72
DOI: https://rdcu.be/bdG3n

Philipp Otto, Wolfgang Schmid, Robert Garthoff (2018): Generalised spatial and spatiotemporal autoregressive conditional heteroscedasticity,  Spatial Statistics Volume 26, August 2018, Pages 125-145
DOI: 10.1016/j.spasta.2018.07.005

Robert Garthoff, Philipp Otto (2018): Verfahren zur Überwachung räumlicher autoregressiver Prozesse mit externen Regressoren,  AStA Wirtschafts- und Sozialstatistisches Archiv Volume 12, Issue 2, pp 107–133
DOI: https://rdcu.be/bdG0S

Philipp Otto (2017): A note on efficient simulation of multidimensional spatial autoregressive processes,  Communications in Statistics - Simulation and Computation Volume 46, 2017 - Issue 6
DOI: 10.1080/03610918.2015.1122050

Anna-Liesa Lange, Philipp Otto (2016): Bayes’sche Statistik in der Dienstleistungsforschung,  AStA Wirtschafts- und Sozialstatistisches Archiv Volume 10, Issue 4, pp 247–267
DOI: https://rdcu.be/bdG4t

Philipp Otto, Wolfgang Schmid (2016): Detection of spatial change points in the mean and covariances of multivariate simultaneous autoregressive models,  Biometrical Journal 58(5). pp. 1113-1137
DOI: 10.1002/bimj.201500148

Robert Garthoff, Philipp Otto (2016): Control charts for multivariate spatial autoregressive models,  AStA Advances in Statistical Analysis Volume 101, Issue 1, pp 67–94
DOI: https://rdcu.be/bdG1S

Philipp Otto (2019): Modeling Spatial Dependence in Local Risks and Uncertainties,  Proceedings of the 29th European Safety and Reliability Conference Weitere Informationen
DOI: 10.3850/978-981-11-2724-3_0890-cd

Rik Gijsman, Philipp Otto, Torsten Schlurmann, Jan Visscher (2019): Statistical analysis of Sylt’s coastal profiles using a spatiotemporal functional model,  Smart Statistics for Smart Applications, Pearson Proceedings, pp. 331-338 Weitere Informationen

Garthoff, R., Otto, P. (2015): Simultaneous surveillance of means and covariances of spatial models,  Springer Proceedings in Mathematics & Statistics, vol. 122, pp. 271-281
DOI: 10.1007/978-3-319-13881-7_30
ISBN: 978-3-319-13881-7

Otto, P. (2010): Evaluation of Innovative Potential (Оценка инновационности страны),  16th International Conference in Economics for Young Researches “Companies and Reforms in Russia

Otto, Philipp, Lange, Anna-Liesa (2017): Arbeitsbuch der Angewandten Statistik,  SpringerGabler

Philipp Otto, Wolfgang Schmid (2019): Spatial and Spatiotemporal GARCH Models -- A Unified Approach
arXiv: 1908.08320

Otto, Philipp (2018): spGARCH: An R-Package for Spatial and Spatiotemporal ARCH models