Publikationen

2016:

• Baran, S. and Möller, A. (2016):
  Bivariate ensemble model output statistics approach for joint forecasting of wind speed and temperature.
  Meteorology and Atmospheric Physics, DOI: 10.1007/s00703-016-0467-8


• Feilke, M., Bischl, B., Schmid, V.J. and Gertheiss, J. (2016): Boosting in Nonlinear Regression Models with an Application to DCE-MRI data. Methods of Information in Medicine, 55, 31-41.


• Hess, W., Tutz, G. and Gertheiss, J. (2016): A flexible link function for discrete-time duration models. Jahrbücher für Nationalökonomie und Statistik (Journal of Economics and Statistics), accepted for publication.


• Meier-Dinkel, L., Gertheiss, J., Schnäckel, W. and D.~Mörlein (2016): Consumers' perception and acceptance of boiled and fermented sausages from strongly boar tainted meat. Meat Science, accepted for publication.


• Möller, A., Groß, J. (2016):
  Probabilistic temperature forecasting based on an ensemble AR modification. Quarterly Journal of the Royal Meteorological Society, 142 (696), 1385-1394. DOI:10.1002/qj.2741


• Sweeney, E., Crainiceanu, C. and Gertheiss, J. (2016): Testing differentially expressed genes in dose-response studies and with ordinal phenotypes. Statistical Applications in Genetics and Molecular Biology, accepted for publication.


• Trautmann, J., Meier-Dinkel, L., Gertheiss, J. and Mörlein, D. (2016): Boar taint detection: A comparison of three sensory protocols. Meat Science, 111, 92-100.


• Tutz, G. and Gertheiss, J. (2016): Regularized regression for categorical data (with discussion). Statistical Modelling, to appear.

2015:

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


• Bartzsch, O., Gertheiss, J. and Calabrese, P. (2015): Wert und Akzeptanz einer Alzheimer-Risikodiagnostik. Der Nervenarzt, to appear.


• Fuchs, K., Gertheiss, J. and Tutz, G. (2015): Nearest Neighbor Ensembles for Functional Data with Interpretable Feature Selection. Chemometrics and Intelligent Laboratory Systems, 146, 186-197.


• Gertheiss, J., Maier, V., Hessel, E.F. and Staicu, A.-M. (2015): Marginal Functional Regression Models for Analyzing the Feeding Behavior of Pigs. Journal of Agricultural, Biological, and Environmental Statistics, 20, 353-370.


• Hasenbeck, F., Reiser, D., Ghendrih, P., Marandet, Y., Tamain, P., Möller, A. and Reiter, D. (2015): Multiscale modeling approach for radial particle transport in large-scale simulations of the tokamak plasma edge. Procedia Computer Science, 51, 1128-1137.


• Meier-Dinkel, L., Gertheiss, J., Müller, S., Wesoly, R. and Mörlein, D. (2015): Evaluating the Performance of Sensory Quality Control: the Case of Boar Taint. Meat Science, 100, 73-84.


• Möller, A. (2015): Spatially adaptive probabilistic temperature forecasting using Markovian EMOS, in H. Friedl and H. Wagner (eds.): Proceedings of the 30th International Workshop on Statistical Modelling, vol. II, 175-178.


• Mörlein, D., Christensen, R.H.B. and Gertheiss, J. (2015): Validation of Boar Taint Detection by Sensory Quality Control: Relationship between Sample Size and Uncertainty of Performance Indicators. Meat Science, 100, 232-236.

2014:

• Bühlmann, P., Gertheiss, J., Hieke, S., Kneib, T., Ma, S., Schuhmacher, M., Tutz, G., Wang, C.-Y., Wang, Z. and Ziegler, A. (2014): Discussion of "The Evolution of Boosting Algorithms" and "Extending Statistical Boosting". Methods of Information in Medicine, 53, 436-445.


• Gertheiss, J. (2014): ANOVA for Factors with Ordered Levels. Journal of Agricultural, Biological, and Environmental Statistics, 19, 258-277.


• Gertheiss, J., Maier, V., Hessel, E.F. and Staicu, A.-M. (2014): Modeling Binary Functional Data with Application to Animal Husbandry, in T. Kneib, F. Sobotka, J. Fahrenholz, and H. Irmer (eds.): Proceedings of the 29th International Workshop on Statistical Modelling, 139-144.


• Hartmann, L., Schulz-Wiemann, C., Spiller, A. and Gertheiss, J. (2014): Weiterentwicklung der Rankingsysteme im Reitsport - ein Experiment. Sportwissenschaft, 44, 99-115.


• Möller, A., Tutz, G. and Gertheiss, J. (2014): Random Forests for Functional Covariates, in T. Kneib, F. Sobotka, J. Fahrenholz, and H. Irmer (eds.): Proceedings of the 29th International Workshop on Statistical Modelling, 219-223.


• Oelker, M.-R., Gertheiss, J. and Tutz, G. (2014): Regularization and Model Selection with Categorical Predictors and Effect Modifiers in Generalized Linear Models. Statistical Modelling, 14, 157-177.


• Sommer, J.C, Gertheiss, J. and Schmid, V.J. (2014): Spatially Regularized Estimation for the Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Data. Statistics in Medicine, 33, 1029-1041.


• Trautmann, J., Gertheiss, J., Wicke, M. and Mörlein, D. (2014): How Olfactory Acuity Affects the Sensory Assessment of Boar Fat: a Proposal for Quantification, Meat Science, 98, 255-262.


• Tutz, G. and Gertheiss, J. (2014): Rating Scales as Predictors - the Old Question of Scale Level and some Answers, Psychometrika, 79, 357-376.

2013:

• Gertheiss, J., Goldsmith, J., Crainiceanu, C. and Greven, S. (2013): Longitudinal Scalar-on-Function Regression with Application to Tractography Data, Biostatistics, 14, 447-461.


• Gertheiss, J. and Kiers, H.A.L. (2013): Penalized Non-Linear Principal Components Analysis for Ordinal Variables, in V.M.R. Muggeo, V. Capursi, G. Boscaino, and G. Lovison (eds.): Proceedings of the 28th International Workshop on Statistical Modelling, 607-610.


• Gertheiss, J., Maity, A. and Staicu, A.-M. (2013): Variable Selection in Generalized Functional Linear Models, Stat, 2, 86-101.


• Gertheiss, J., Stelz, V. and Tutz, G. (2013): Regularization and Model Selection with Categorical Covariates, in B. Lausen, D. Van den Poel, and A. Ultsch (eds.): Algorithms from and for Nature and Life, Berlin/Heidelberg: Springer, 215-222.


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