PUB - Publikationen an der Universität Bielefeld

Alle markieren

• [19]
  

  2024 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2986291

  Gross, J., & Möller, A.C., 2024. Some additional remarks on statistical properties of Cohen's d in the presence of covariates. Statistical Papers .

  PUB | DOI | WoS
   
• [18]
  

  2023 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2982406

  Jobst, D., Möller, A.C., & Gross, J., 2023. D-vine-copula-based postprocessing of wind speed ensemble forecasts. Quarterly Journal of the Royal Meteorological Society.

  PUB | PDF | DOI | WoS
   
• [17]
  

  2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2981385

  Demaeyer, J., et al., 2023. The EUPPBench postprocessing benchmark dataset v1.0. Earth System Science Data, 15(6), p 2635-2653.

  PUB | DOI | WoS
   
• [16]
  

  2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2969855

  Groß, J., & Möller, A.C., 2023. A Note on Cohen's d From a Partitioned Linear Regression Model. Journal of Statistical Theory and Practice, 17(2): 22.

  PUB | DOI | WoS
   
• [15]
  

  2022 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2966732

  Möller, A.C., George, A.C., & Gross, J., 2022. Predicting school transition rates in Austria with classification trees. International Journal of Research & Method in Education .

  PUB | DOI | WoS
   
• [14]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2959842

  Lerch, S., et al., 2020. Simulation-based comparison of multivariate ensemble post-processing methods. Nonlinear Processes in Geophysics, 27(2), p 349-371.

  PUB | PDF | DOI | Download (ext.) | WoS | Preprint
   
• [13]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2959843

  Möller, A.C., & Groß, J., 2020. Probabilistic temperature forecasting with a heteroscedastic autoregressive ensemble postprocessing model. Quarterly Journal of the Royal Meteorological Society, 146(726), p 211-224.

  PUB | PDF | DOI | Download (ext.) | WoS | Preprint
   
• [12]
  

  2020 | Datenpublikation | PUB-ID: 2959845

  Lerch, S., et al., 2020. Supplementary material to "Simulation-based comparison of multivariate ensemble post-processing methods", Copernicus GmbH.

  PUB | Dateien verfügbar | DOI
   
• [11]
  

  2020 | Zeitungsartikel | Veröffentlicht | PUB-ID: 2960084

  Baran, S., & Möller, A.C., 01.04.2020 Various Approaches to Statistical Calibration of Ensemble Weather Forecasts. ERCIM News, (121), p 30-31.

  PUB | Download (ext.)
   
• [10]
  

  2019 | Wissenschaftliche Software | PUB-ID: 2960075

  Groß, J., & Möller, A.C., 2019. ensAR - Autoregressive postprocessing methods for ensemble forecasts, GitHub.

  PUB | Dateien verfügbar
   
• [9]
  

  2018 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2960074

  Möller, A.C., & Schefzik, R., 2018. Ensemble Postprocessing Methods Incorporating Dependence Structures. In S. Vannitsem, D. Wilks, & J. Messner, eds. Statistical Postprocessing of Ensemble Forecasts. 1st ed. Elsevier, pp. 362.

  PUB
   
• [8]
  

  2018 | Preprint | PUB-ID: 2960072

  Möller, A.C., et al., 2018. Vine copula based post-processing of ensemble forecasts for temperature. arXiv:1811.02255.

  PUB | arXiv
   
• [7]
  

  2017 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2960066

  Baran, S., & Möller, A.C., 2017. Bivariate ensemble model output statistics approach for joint forecasting of wind speed and temperature. Meteorology and Atmospheric Physics, 129(1), p 99-112.

  PUB | DOI | Download (ext.) | WoS
   
• [6]
  

  2016 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2960067

  Möller, A.C., Tutz, G., & Gertheiss, J., 2016. Random forests for functional covariates. Journal of Chemometrics, 30(12), p 715-725.

  PUB | DOI | Download (ext.) | WoS
   
• [5]
  

  2016 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2960068

  Möller, A.C., & Groß, J., 2016. Probabilistic temperature forecasting based on an ensemble autoregressive modification. Quarterly Journal of the Royal Meteorological Society, 142(696), p 1385-1394.

  PUB | DOI | Download (ext.) | WoS
   
• [4]
  

  2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2960070

  Baran, S., & Möller, A.C., 2015. Joint probabilistic forecasting of wind speed and temperature using Bayesian model averaging. Environmetrics, 26(2), p 120-132.

  PUB | DOI | Download (ext.) | WoS
   
• [3]
  

  2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2960069

  Hasenbeck, F., et al., 2015. Multiscale Modeling Approach for Radial Particle Transport in Large-scale Simulations of the Tokamak Plasma Edge. Procedia Computer Science, 51, p 1128-1137.

  PUB | DOI | Download (ext.)
   
• [2]
  

  2015 | Preprint | PUB-ID: 2960073

  Möller, A.C., et al., 2015. Spatially adaptive, Bayesian estimation for probabilistic temperature forecasts. arXiv:1507.05066.

  PUB | arXiv
   
• [1]
  

  2013 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2960071

  Möller, A.C., Lenkoski, A., & Thorarinsdottir, T.L., 2013. Multivariate probabilistic forecasting using ensemble Bayesian model averaging and copulas. Quarterly Journal of the Royal Meteorological Society, 139(673), p 982-991.

  PUB | DOI | Download (ext.) | WoS