Inhaltsbereich
Further publications
- Wegener, M. and Kauermann, G. (2015):
Forecasting in Nonlinear Univariate Time Series using Penalized Splines.
Statistical Papers 58(3): 557–576. doi:10.1007/s00362-015-0711-1.
- Schulze Waltrup, L., Sobotka, F., Kneib, T. and Kauermann, G. (2014):
Expectile and Quantile Regression - David and Goliath?
Statistical Modelling 15(5): 433-456. doi:10.1177/1471082X14561155.
- Kauermann, G. and Schellhase, C. (2014):
Flexible Pair-Copula Estimation in D-vines with Penalized Splines.
Statistics and Computing 24(6): 1081-1100.
- Sabanés Bové, D., Held, L. and Kauermann, G. (2014):
Objective Bayesian Model Selection in Generalised Additive Models with Penalised Splines.
Journal of Computational and Graphical Statistics 24(2): 394-415. doi:10.1080/10618600.2014.912136.
- Kauermann, G. and Meyer, R. (2014):
Penalized Marginal Likelihood Estimation of Finite Mixtures of Archimedean Copulas.
Computational Statistics 29(1-2): 283-306.
- Kauermann, G. and Kuhlenkasper, T. (2013):
Penalized Splines and Multilevel Models.
Handbook of Multilevel Modelling, Editors: Marc Scott, Jeffrey Simonoff and Brian Marx. SAGE Publications.
- Kauermann, G., Schellhase, C. and Ruppert, D. (2013):
Flexible Copula Density Estimation with Penalized Hierarchical B-Splines.
Scandinavian Journal of Statistics 40(4), 685-703.
- Sobotka, F., Kauermann, G., Schulze Waltrup, L. and Kneib, T. (2013):
On Confidence Intervals for Geoadditive Expectile Regression Models.
Statistics and Computing 23(2), 135-148.
- Mestekemper, T., Kauermann, G. and Smith, M. (2013):
A Comparison of Periodic Autoregressive and Dynamic Factor Models in Intraday Energy Demand Forecasting.
International Journal of Forecasting 29(1), 1-12.
- Kauermann, G., Haupt, H. and Kaufmann, N. (2012):
A Hitchhiker's View on Spatial Statistics and Spatial Econometrics for Lattice Data.
Statistical Modelling 12(5), 419-440.
- Kauermann, G. and Westerheide, N. (2012):
To move or not to move to find a new job - Spatial Duration Time Model with Dynamic Covariate Effects.
Journal of Applied Statistics 39(5), 995-1009.
- Schellhase, C. and Kauermann, G. (2012):
Density Estimation and Comparison with a Penalized Mixture Approach.
Computational Statistics 27(4), 757-777.
- Westerheide, N. and Kauermann, G. (2012):
Flexible Modelling of Duration of Unemployment Using Functional Hazard Models and Penalized Splines: A Case Study Comparing Germany and the UK.
Studies in Nonlinear Dynamics & Econometrics 16(1), Article 5.
- Kauermann, G., Teuber, T. and Flaschel, P. (2012):
Exploring US Business Cycles with Bivariate Loops using Penalized Spline Regression.
Computational Economics, 39, 409-427.
- Kauermann, G. and Mestekemper, T. (2012):
A short note on quantifying and visualizing yearly variation in online monitored temperature data.
Statistical Modelling: An International Journal, 12, 195-209.
- Smith, M. and Kauermann, G. (2011):
Bicycle Commuting in Melbourne during the 2000s Energy Crisis: A Semiparametric Analysis of Intraday Volumes.
Transportation Research Part B: Methodological, 45, 1846-1862.
- Kauermann, G., Krivobokova, T. and Semmler, W. (2011):
Filtering Time Series with Penalized Splines.
Studies in Nonlinear Dynamics & Econometrics, 15(2), Article 2.
- Kauermann, G. and Opsomer, J.D. (2011):
Data-driven Selection of the Spline Dimension in Penalized Spline Regression.
Biometrika, 98(1), 225-230.
- Kauermann, G. and Wegener, M. (2011):
Functional Variance Estimation using Penalized Splines with Principal Component Analysis.
Statistics and Computing, 21, 159-172.
- Kuhlenkasper, T. and Kauermann, G. (2010):
Duration of maternity leave in Germany: A case study of nonparametric hazard models and penalized splines.
Labour Economics, 17(3), 466-473.
- Mestekemper, T., Windmann, M. and Kauermann, G. (2010):
Functional Hourly Forecasting of Water Temperature.
International Journal of Forecasting 26(4), 684-699.
- Kauermann, G., Ormerod, J. and Wand, M.P. (2010):
Parsimonious Classification via Generalized Linear Mixed Models.
Journal of Classification 27(1), 89-110.
- Mikolajczyk, R. T., Kauermann, G., Sagel, U. and Kretschmar, M. (2009):
A Mixture Model to Assess the Extent of Cross-Transmission of Multi-Resistant Pathogens in Hospitals.
Infection Control and Hospital Epidemiology, 30(8), 730-736.
- Flaschel, P., Groh, G., Kauermann, G. and Teuber, T. (2009):
The Classical growth cycle after fifteen years of new observations.
In: P. Flaschel and M. Landesmann (Eds.): Mathematical Economics and the Dynamics of Capitalism. London: Routledge. 69-77.
- Becher, H., Kauermann, G., Khomski, P. and Kouyate, B. (2009):
Using penalized splines to model age- and season-of-birthdependent effects of childhood mortality risk factors in rural Burkina Faso.
Biometrical Journal 51(1), 110-122.
- Kauermann, G. and Khomski, P. (2009):
Full Time or Part Time Reemployment: A Competing Risk Model with Frailties and Smooth Effects using a Penalty based Approach.
Journal of Computational and Graphical Statistics 18(1), 106-125.
- Kauermann, G., Claeskens, G. and Opsomer, J. D. (2009):
Bootstrapping for Penalized Spline Regression.
Journal of Computational and Graphical Statistics 18(1), 126-146.
- Kauermann, G., Krivobokova, T. and Fahrmeir, L. (2009):
Some Asymptotic Results on Generalized Penalized Spline Smoothing.
Journal of the Royal Statistical Society, Series B 71(2), 487-503.
- Kauermann, G. and Norrie, J. (2008):
Generalized Linear Models.
Encyclopaedia of Clinical Trials. Wiley.
- Krivobokova, T., Crainiceanu, C.M. and Kauermann, G. (2008):
Fast Adaptive Penalized Splines.
Journal of Computational and Graphical Statistics 17(1), 1-20.
- Greiner, A., Kauermann, G. (2008):
Dept policy in Euro-area countries: Evidence for Germany and Italy using penalized spline smoothing.
Economic Modelling 25 (6), 1144-1154.
- Wegener, M. and Kauermann, G. (2008):
Modelling Equity Risk Premium using Penalized Splines.
Advances in Statistical Analysis 92, 35-56.
- Kauermann, G., Xu, R. and Vaida, F. (2008):
Stacked Laplace-EM Algorithm for Duration Models with Time-Varying and Random Effects.
Computational Statistics and Data Analysis 52, 2514-2528.
- Opsomer, J.D., Claeskens, G., Ranalli, G., Kauermann, G. and Breidt, F.J. (2008):
Nonparametric small area estimation using penalized spline regression.
Journal of the Royal Statistical Society, Series B 70, 265-286.
- Flaschel, P., Kauermann, G. and Semmler, W. (2007):
Testing Wage and Price Phillips Curves for the United States.
Metroeconomica 58(4), 550-581.
- Eisenbeiss, M., Kauermann, G. and Semmler, W. (2007):
Estimating Beta-Coefficients of German Stock Data: A Non-parametric Approach.
The European Journal of Finance 13, (6), 503-522.
- Windmann, M. and Kauermann, G. (2007):
Statistical Consulting at German Universities - Results of a Survey.
Advances in Statistical Analysis 91, 367-378.
- Krivobokova, T. and Kauermann, G. (2007):
A Note on Penalized Spline Smoothing with Correlated Errors.
Journal of the American Statistical Association 102, 1328-1337.
- Wager, C., Vaida, F. and Kauermann, G. (2007):
Model Selection for P-Spline Smoothing using Akaike Information Criteria.
Australian and New Zealand Journal of Statistics 49(2), 173-190.
- Greiner, A., Kauermann, G. (2007):
Sustainability of US public debt: Estimating smoothing spline regression.
Economic Modelling 24, 250-364.
- Brown, D., Kauermann, G. and Ford, I. (2007):
A partial likelihood approach to the smooth estimation of dynamic covariate effects.
Biometrical Journal 49, 441-452.
- J.D. Opsomer, F.J. Breidt, G.G. Moisen and G. Kauermann (2007):
Model-assisted estimation of forest resources with generalized additive models (with discussion).
Journal of the American Statistical Association 102, 400-416.
- Kauermann, G. and Khomski, P. (2006):
Additive Two Way Hazards Model with Varying Coefficients.
Computational Statistics and Data Analysis 51 (3), 1944-1956.
- Kauermann, G. (2006):
Nonparametric models and their estimation.
Allgemeines Statistisches Archiv 90, 135-150.
- Krivobokova, T., Kauermann, G. and Archontakis, T. (2006):
Estimating the term structure of interest rates using penalized splines.
Statistical Papers, 47(3): 443-459.
- Flaschel, P., Kauermann, G. and Teuber, T. (2005):
Long Cycles in employment, inflation and real unit wage costs. Qualitative analysis and quantitative assessment.
American Journal of Applied Science (Special Issue), 69-77.
- Kauermann, G., Tutz, G. and Brüderl, J. (2005):
The survival of newly founded firms: A case study into varying-coefficient models.
Journal of the Royal Statistical Society, Series A, 168, 145-158.
- Kauermann, G. (2005):
Penalised Spline Fitting in Multivariable Survival Models with Varying Coefficients.
Computational Statistics and Data Analysis, 49, 169-186.
- Kauermann, G. (2005):
A note on smoothing parameter selection for penalised spline smoothing.
Journal of Statistical Planing and Inference, 127, 53-69.
- Kauermann, G. and Eilers, P. (2004):
Modelling microarray data using a threshold mixture model.
Biometrics, 60, 376-387.
- Kauermann, G. and Opsomer, J. (2004):
Generalized Cross-validation for Bandwidth Selection of Backfitting Estimates in Generalized Additive Models.
Journal of Computational and Graphical Statistics, 13, 66-89.
- Kauermann, G. and Ortlieb, R. (2004):
Temporal pattern in the number of staff on sick leave: The effect of downsizing.
Journal of the Royal Statistical Society, Series C - Applied Statistics, 53, 353-367.
- Kauermann, G. and Berger, U. (2003):
A smooth test in proportional hazard models using local partial likelihood fitting.
ifetime Data Analysis, 9, 373-393.
- Einbeck, J. and Kauermann, G. (2003):
Online Monitoring with Local Smoothing Methods and Adaptive Ridging.
Journal of Statistical Computation and Simulation, 73, No. 12, 913-929.
- Kauermann, G. and Opsomer, J. (2003):
Local likelihood estimation in Generalized Additive Models.
Scandinavian Journal of Statistics, 30, 317-337.
- Tutz, G. and Kauermann, G. (2003):
Generalized linear random effect models with varying coefficients.
Computational Statistics and Data Analysis, 43, 13-28 .
- Kauermann, G. and Küchenhoff, H. (2003):
Modelling Data from Inside of Earth: Local Smoothing of Mean and Dispersion Structure in Deep Drill Data.
Statistical Modelling: An International Journal, 3, 43-64.
- Kauermann, G. and Tutz, G. (2003):
Semi- and nonparametric modelling of ordinal data.
Journal of Computational and Graphical Statistics, 12, 176-196.
- Kauermann, G. (2002):
On a Small Sample Adjustment for the Profile Score Function in Semiparametric Smoothing Models.
Journal of Multivariate Analysis, 82, 471-485.
- Kauermann, G. and Carroll, R.J. (2001):
A note on the efficiency of sandwich covariance matrix estimation.
Journal of the American Statistical Association, 96, 1387-1396.
- Kauermann, G. and Tutz, G. (2001):
Testing generalized linear and semiparametric models against smooth alternatives.
Journal of the Royal Statistical Society, Series B, 63, 147-166.
- Galindo, C., Kauermann, G., Liang, H. and Carroll, R. (2001):
Bootstrap confidence intervals for local likelihood, local estimating equations and varying coefficient models.
Statistica Sinica, 11, 121-134.
- Friedl, H. and Kauermann, G. (2000):
Standard errors for EM estimates in variance component models.
Biometrics, 56, 761-767
- Kauermann, G. (2000):
Modeling longitudinal data with ordinal response by varying coefficients.
Biometrics, 56, 692-698.
- Kauermann, G. and Tutz, G. (2000):
Local likelihood estimation in varying-coefficient models including additive bias correction.
Journal of Nonparametric Statistics, 12, 343-371.
- Kauermann, G. and Tutz, G. (1999):
On model diagnostics using varying coefficient models.
Biometrika, 86, 119-128.
- Kauermann, G., Müller, M. and Carroll, R.J. (1998):
The efficiency of bias-corrected estimators for nonparametric kernel estimation based on local estimation equations.
Statistics & Probability Letters, 37, 41-47.
- Kauermann, G. (1997):
A note on multivariate logistic models for contingency tables.
Australian Journal of Statistics, 39, 261-276.
- Tutz, G. and Kauermann, G. (1997):
Local estimators in multivariate generalized linear models with varying coefficients.
Computational Statistics, 12, 193-208.
- Kauermann, G. (1996):
On a dualization of graphical Gaussian models.
Scandinavian Journal of Statistics, 23, 105-116.
