Publikationsliste
Holz, S.; Coblenz, M.; Koch, R.; Bauer, H.-J.; Grothe, O. (2024). Two approaches for constructing multivariate injection models for prefilming airblast atomizers. International Journal of Multiphase Flow, 181, 104999. doi:10.1016/j.ijmultiphaseflow.2024.104999
Grothe, O.; Rieger, J. (2024). Decomposition and graphical correspondence analysis of checkerboard copulas. Dependence Modeling, 12 (1), Art.-Nr.: 20240006. doi:10.1515/demo-2024-0006
Rieger, J. B. (2024, Juli 31). Dependence in Statistical Data Analysis: From Structural Insights Through Decomposition to the Combination of Forecasts and the Evaluation of Tracking Changes. Dissertation. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000172962
Liu, B.; Coblenz, M.; Grothe, O. (2024). Predicting grid frequency short-term dynamics with Gaussian processes and sequence modeling. e-Energy ’24: Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems, 535–550, Association for Computing Machinery (ACM). doi:10.1145/3632775.3662160
Borlinghaus, P.; Tausch, F.; Odemer, R. (2024). Natural color dispersion of corbicular pollen limits color-based classification. ISPRS Open Journal of Photogrammetry and Remote Sensing, 12, Article no: 100063. doi:10.1016/j.ophoto.2024.100063
Kächele, F.; Schneider, N. (2024). Cluster Validation Based on Fisher’s Linear Discriminant Analysis. Journal of Classification. doi:10.1007/s00357-024-09481-3
Valgaev, O. (2023, November 28). Day-Ahead Building Power Demand Forecasting in Smart Grids. Dissertation. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000164778
Kächele, F. (2023, Oktober 10). Developments in Theory and Application of Copulas: Variance Estimation, Economic Modeling, Forecasting and Machine Learning. Dissertation. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000162773
Borlinghaus, P.; Jung, J.; Odemer, R. (2023). Introducing Pollenyzer: An app for automatic determination of colour diversity for corbicular pollen loads. Smart Agricultural Technology, 5, Art.-Nr.: 100263. doi:10.1016/j.atech.2023.100263
Holz, S. (2023, August 1). Multivariate Statistische Modellierung der Tropfenstartbedingungen für Euler-Lagrange-Simulationen von Triebwerksbrennkammern. Dissertation. Logos Verlag Berlin.
Watermeyer, M. (2023, Juli 7). Advancing Energy Transition: Statistical Approaches to Pan-European Feed-in Data Sets, Enhanced Data Quality and Improved Forecasting. Dissertation. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000160201
Kächele, F.; Grothe, O. (2023). Realtime temperature-adjusted natural gas savings of European private households: A study on the German gas market in 2022. Companion Proceedings of the 14th ACM International Conference on Future Energy Systems (e-Energy ’23), 21–25, Association for Computing Machinery (ACM). doi:10.1145/3599733.3600246
Grothe, O.; Kächele, F.; Krüger, F. (2023). From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting. Energy Economics, 120, Art.-Nr.: 106602. doi:10.1016/j.eneco.2023.106602
Borlinghaus, P.; Tausch, F.; Rettenberger, L. (2023). A Purely Visual Re-ID Approach for Bumblebees (Bombus terrestris). Smart Agricultural Technology, 3, Art.-Nr.: 100135. doi:10.1016/j.atech.2022.100135
Möbius, T.; Watermeyer, M.; Grothe, O.; Müsgens, F. (2023). Enhancing energy system models using better load forecasts. Energy Systems. doi:10.1007/s12667-023-00590-3
Mohr, R.; Coblenz, M.; Kirst, P. (2023). Globally optimal univariate spline approximations. Computational Optimization and Applications, 85, 409–439. doi:10.1007/s10589-023-00462-7
Grothe, O.; Rieger, J. (2022). SVD-reduction of high-dimensional German spatio-temporal wind speed data and clusters of similarity. e-Energy ’22: Proceedings of the Thirteenth ACM International Conference on Future Energy Systems, 515–520, Association for Computing Machinery (ACM). doi:10.1145/3538637.3539764
Borlinghaus, P.; Odemer, R.; Tausch, F.; Schmidt, K.; Grothe, O. (2022). Honey bee counter evaluation – Introducing a novel protocol for measuring daily loss accuracy. Computers and Electronics in Agriculture, 197, Art.Nr. 106957. doi:10.1016/j.compag.2022.106957
Koster, N.; Grothe, O.; Rettinger, A. (2022). Signing the Supermask: Keep, Hide, Invert. International Conference on Learning Representations 2022.
Coblenz, M.; Grothe, O.; Herrmann, K.; Hofert, M. (2022). Smooth bootstrapping of copula functionals. Electronic Journal of Statistics, 16 (1), 2550–2606. doi:10.1214/22-EJS2007
Grothe, O.; Kächele, F.; Schmid, F. (2022). A multivariate extension of the Lorenz curve based on copulas and a related multivariate Gini coefficient. The Journal of Economic Inequality, 20 (3), 727–748. doi:10.1007/s10888-022-09533-x
Grothe, O.; Kächele, F.; Watermeyer, M. (2022). Analyzing Europe’s Biggest Offshore Wind Farms: A Data Set with 40 Years of Hourly Wind Speeds and Electricity Production. Energies, 15 (5), Art.-Nr.: 1700. doi:10.3390/en15051700
Coblenz, M.; Grothe, O.; Herrmann, K.; Hofert, M. (2021). Smooth bootstrapping of copula functionals. doi:10.48550/arXiv.2110.03397
Grothe, O.; Kächele, F.; Schmid, F. (2021). A multivariate extension of the Lorenz curve based on copulas and a related multivariate Gini coefficient. Springer. doi:10.48550/arXiv.2101.04748
Coblenz, M.; Holz, S.; Bauer, H.-J.; Grothe, O.; Koch, R. (2020). Modelling fuel injector spray characteristics in jet engines by using vine copulas. Journal of the Royal Statistical Society / C, 69 (4), 863–886. doi:10.1111/rssc.12421
Grothe, O.; Kaplan, A.; Kouz, K.; Saugel, B. (2020). Computer Program for Error Grid Analysis in Arterial Blood Pressure Method Comparison Studies. Anesthesia & analgesia, 130 (3), e71–e74. doi:10.1213/ANE.0000000000004584
Grothe, O.; Kleppe, T. S.; Liesenfeld, R. (2019). The Gibbs sampler with particle efficient importance sampling for state-space models*. Econometric reviews, 38 (10), 1152–1175. doi:10.1080/07474938.2018.1536098
Bethge, D.; Chen, J.; Grothe, O.; Elmer, J.; Dubrawski, A. (2019). Prognostication of neurological recovery by analyzing structural breaks in EEG data. 2019 International Conference on Data Mining Workshops (ICDMW), 933–940, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICDMW.2019.00136
Axenovich, M.; Kaplan, A.; Yuster, R. (2019). Clumsy packings of graphs. The electronic journal of combinatorics, 26 (2), Art.Nr.: P2.39.
Grothe, O.; Kaplan, A.; Kouz, K.; Saugel, B. (2019). Software and example data for error grid analysis. doi:10.5445/IR/1000096054
Rogge, D. E.; Nicklas, J. Y.; Schön, G.; Grothe, O.; Haas, S. A.; Reuter, D. A.; Saugel, B. (2019). Continuous Noninvasive Arterial Pressure Monitoring in Obese Patients During Bariatric Surgery: An Evaluation of the Vascular Unloading Technique (Clearsight system). Anesthesia & analgesia, 128 (3), 477–483. doi:10.1213/ANE.0000000000003943
Coblenz, M.; Grothe, O.; Schreyer, M.; Trutschnig, W. (2018). On the length of copula level curves. Journal of multivariate analysis, 167, 347–365. doi:10.1016/j.jmva.2018.06.001
Breig, R.; Coblenz, M.; Pelz, M. (2018). Enhancing simulation-based theory development in entrepreneurship through statistical validation. Journal of Business Venturing Insights, 9, 53–59. doi:10.1016/j.jbvi.2018.02.003
Saugel, B.; Grothe, O.; Nicklas, J. Y. (2018). Error Grid Analysis for Arterial Pressure Method Comparison Studies. Anesthesia & analgesia, 126 (4), 1177–1185. doi:10.1213/ANE.0000000000002585
Coblenz, M.; Dyckerhoff, R.; Grothe, O. (2018). Nonparametric Estimation of Multivariate Quantiles. Environmetrics, 29 (2), Art. Nr.: e2488. doi:10.1002/env.2488
Coblenz, M. (2018). Advances in Dependence Modeling: Multivariate Quantiles, Copula Level Curve Lengths, and Non-Simplified Vine Copulas. Dissertation. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000088365
Coblenz, M.; Dyckerhoff, R.; Grothe, O. (2018). Confidence Regions for Multivariate Quantiles. Water, 10 (8), Article: 996. doi:10.3390/w10080996
Kaso, M.; Musgens, F.; Grothe, O. (2016). Dynamic forecast combinations of improved individual forecasts for the prediction of wind energy. 13th International Conference on the European Energy Market (EEM), Porto, Portugal, 6–9 June 2016, Art.Nr. 7521228, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/EEM.2016.7521228
Grothe, O.; Hofert, M. (2015). Construction and sampling of Archimedean and nested Archimedean Lévy copulas. Journal of multivariate analysis, 138, 182–198. doi:10.1016/j.jmva.2014.12.004
Saugel, B.; Grothe, O.; Wagner, J. Y. (2015). Tracking changes in cardiac output: Statistical considerations on the four-quadrant plot and the polar plot methodology. Anesthesia & analgesia, 121 (2), 514–524. doi:10.1213/ANE.0000000000000725
Ejsing, J.; Grothe, M.; Grothe, O. (2015). Liquidity and credit premia in the yields of highly-rated sovereign bonds. Journal of empirical finance, 33, 160–173. doi:10.1016/j.jempfin.2015.04.001
Münnix, M. C.; Schäfer, R.; Grothe, O. (2014). Estimating correlation and covariance matrices by weighting of market similarity. Quantitative finance, 14 (5), 931–939. doi:10.1080/14697688.2011.605075
Eichler, M.; Grothe, O.; Manner, H.; Tuerk, D. (2014). Models for short-term forecasting of spike occurrences in Australian electricity markets: a comparative study. The journal of energy markets, 7 (1), 55–81.
Grothe, O.; Korniichuk, V.; Manner, H. (2014). Modeling Multivariate Extreme Events Using Self-Exciting Point Processes. Journal of econometrics, 182 (2), 269–289. doi:10.1016/j.jeconom.2014.03.011
Blumentritt, T.; Grothe, O. (2013). Ranking ranks: a ranking algorithm for bootstrapping from the empirical copula. Computational statistics, 28 (2), 455–462. doi:10.1007/s00180-012-0310-8
Grothe, O. (2013). Jump Tail Dependence in Lévy Copula Models. Extremes, 16 (3), 303–324. doi:10.1007/s10687-012-0162-1
Grothe, O.; Müsgens, F. (2013). The influence of spatial effects on wind power revenues under direct marketing rules. Energy policy, 58, 237–247. doi:10.1016/j.enpol.2013.03.004
Grothe, O. (2013). A higher order correlation unscented Kalman filter. Applied mathematics and computation, 219 (17), 9033–9042. doi:10.1016/j.amc.2013.03.019
Grothe, O.; Nicklas, S. (2013). Vine Constructions of Lévy Copulas. Journal of multivariate analysis, 119, 1–15. doi:10.1016/j.jmva.2013.04.002
Grothe, O.; Schnieders, J.; Segers, J. (2013). Measuring association and dependence between random vectors. Journal of multivariate analysis, 123, 96–110. doi:10.1016/j.jmva.2013.08.019
Grothe, O.; Schnieders, J. (2012). Historische Analysen für Offshore-Windanlagen: Analyseverfahren mit Hilfe von Satellitendaten. Emw, (4), online.
Grothe, O.; Schmid, F. (2011). Kendall’s W reconsidered. Communications in statistics / Simulation and computation, 40 (2), 285–305. doi:10.1080/03610918.2010.538791
Grothe, O.; Schnieders, J. (2011). Spatial dependence in wind and optimal wind power allocation: a copula based analysis. Energy policy, 39 (9), 4742–4754. doi:10.1016/j.enpol.2011.06.052
Teschner, F.; Coblenz, M.; Weinhardt, C. (2011). Short-selling in prediction markets. Journal of Prediction Markets, 5 (2), 14–31.
Grothe, O.; Schmidt, R. (2010). Scaling of Levy-Student processes. Physica / A, 389 (7), 1455–1463. doi:10.1016/j.physa.2009.11.039
Grothe, O.; Müller, C.; Gundolf, S. (2007). Liquiditätsrisiken statt Preisrisiken: Steuerung von Clearingzahlungen bei Future-Portfolios. Emw, (6), online.
Grothe, O.; Singer, H. (2006). Bayesian Estimation of Volatility with Moment-Based Nonlinear Stochastic Filters. Fernuniversität.
Deitmar, H.; Denz, C.; Eversloh, M.; Grothe, O.; Holtmann, F.; Krishnamachari, V. V.; Wördemann, M. (2006). Echtzeitbestimmung von Geschwindigkeits- und Dichtefeldern in Mikroströmungen mit Hilfe optisch nichtlinearer Bildaufnahme. Lasermethoden in der Strömungsmesstechnik : 14. Fachtagung, 5. - 7. September 2006, Physikalisch-Technische Bundesanstalt, Braunschweig. Hrsg.: D. Dopheide, 49/1–6, Deutschen Gesellschaft für Laser-Anemometrie.
Deitmar, H.; Denz, C.; Eversloh, M.; Grothe, O.; Holtmann, F.; Krishnamachari, V. V.; Wördemann, M. (2006). Measurement of Density Changes in Fluid Flow by an Optical Nonlinear Filtering Technique. 12th international symposium on flow visualization : September 10-14, 2006, Göttingen, Germany ; CD-Rom proceedings. Ed.: I. Grant, CD-ROM, Optimage Ltd.
Grothe, O.; Müller, C.; Müsgens, F. (2006). Modellierung von Energiepreisrisiken durch Bindefristen bei öffentlichen Ausschreibungen. Emw, (6), online.
Deitmar, H.; Denz, C.; Grothe, O.; Krishnamachari, V. V. (2005). Novelty Filtering with a Photorefractive Lithium-Niobate Crystal. Applied physics letters, 87 (7), Art. Nr. 071105. doi:10.1063/1.2007857