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Publikationen / Publications

2016

  • C. Dion, S. Hermann and A. Samson. Mixedsde: an R Package to Fit Mixed Stochastic Differential Equations. hal-01305574, 2016.
  • C. Dion, A. Samson and S. Hermann. mixedsde: Estimation Methods for Stochastic Differential Mixed Effects Models, 2016. R package version 1.0.
  • S. Hermann. Bayesian prediction for stochastic process models in reliability. Dissertation, TU Dortmund, 2016. [DOI]
  • S. Hermann. BaPreStoPro: an R Package for Bayesian Prediction of Stochastic Processes. SFB 823 Discussion Paper 28/2016, 2016.
  • S. Hermann. Bayesian Prediction for Stochastic Processes based on the Euler Approximation Scheme. SFB 823 Discussion Paper 27/2016, 2016.
  • S. Hermann. BaPreStoPro: Bayesian Prediction of Stochastic Processes, 2016. R package version 0.1.
  • S. Hermann, K. Ickstadt and Ch. H. Müller. Bayesian Prediction for a Jump Diffusion Process with Application to Crack Growth in Fatigue Experiments. Reliability Engineering & System Safety, 2016. [DOI]
  • S. Hermann, K. Ickstadt and Ch. H. Müller. Bayesian Prediction of Crack Growth Based on a Hierarchical Diffusion Model. Applied Stochastic Models in Business and Industry, vol. 32 no. 4, pages 494-510, 2016. [DOI]
  • S. Hermann and F. Ruggeri. Modeling Wear in Cylinder Liners. Quality and Reliability Engineering International, 2016. [DOI]
  • Ch.P. Kustosz, A. Leucht and Ch.H. Müller. Tests based on simplicial depth for AR(1) models with explosion. Journal of Time Series Analysis, 2016. accepted.
  • Ch.P. Kustosz, Ch.H. Müller and M. Wendler. Simplified simplicial depth for regression and autoregressive growth processes. Journal of Statistical Planning and Inference, vol. 173, pages 125-146, 2016. [DOI]

2015

  • G. Heeke, S. Hermann, J. Heinrich, K. Ickstadt, R. Maurer and C.H. Müller. Stochastic modeling and statistical analysis of fatigue tests on prestressed concrete beams under cyclic loadings. SFB 823 Discussion Paper 25/2015, 2015.
  • S. Hermann, K. Ickstadt and Ch.H. Müller. Bayesian prediction for a jump diffusion process with application to crack growth in fatigue experiments.. SFB 823 Discussion Paper 30/2015, 2015.
  • S. Hermann, K. Ickstadt and Ch.H. Müller. Bayesian prediction of crack growth based on a hierarchical diffusion model. SFB 823 Discussion Paper 4/2015, 2015.
  • Ch.H. Müller, S. Szugat, N. Celik and B.R. Clarke. Influence functions of trimmed likelihood estimators for lifetime experiments. Statistics, 2015. [DOI]

2014

  • L. Denecke and Ch.H. Müller. Consistency of the likelihood depth estimator for the correlation coefficient. Statistical Papers, vol. 55, pages 3-13, 2014.
  • L. Denecke and Ch.H. Müller. New robust tests for the parameters of the Weibull distribution for complete and censored data. Metrika, vol. 77, pages 585-607, 2014.
  • G. M. Fröhlich, S. Redwood, R. Rakhit, P. A. MacCarthy, P. Lim, T. Crake, S. K. White, C. J. Knight, C. Kustosz, G. Knapp and others. Long-term survival in patients undergoing percutaneous interventions with or without intracoronary pressure wire guidance or intracoronary ultrasonographic imaging: a large cohort study. JAMA internal medicine, vol. 174 no. 8, pages 1360-1366, 2014.
  • Ch.P. Kustosz and Ch.H. Müller. Analysis of crack growth with robust, distributionfree estimators and tests for nonstationary autoregressive processes. Statistical Papers, vol. 55, pages 125-140, 2014.

2013

  • Ch.H. Müller. Robustness and Complex Data Structures. Festschrift in Honour of Ursula Gather, chapter Upper and lower bounds for breakdown points, pages 67-84. Springer, Berlin, Heidelberg, 2013.
  • Ch.H. Müller. mODa 10 - Advances in Model-Oriented Design and Analysis, chapter D-optimal designs for lifetime experiments with exponential distribution and censoring, pages 179-186. Physica-Verlag, Heidelberg, 2013.
  • Ch.H. Müller and L. Denecke. Stochastik in den Ingenieurwissenschaften - Eine Einführung mit R. Springer, Berlin, 2013.

2012

  • L. Denecke and Ch.H. Müller. Consistency and robustness of tests and estimators based on depth. J. Statist. Plann. Inference, vol. 142, pages 2501-2517, 2012.
  • C. Gunkel, A. Stepper, A.C. Müller and Ch.H. Müller. Micro crack detection with Dijkstra's shortest path algorithm. Machine Vision and Applications, vol. 23, pages 589-601, 2012.

2011

  • L. Denecke and Ch.H. Müller. Robust estimators and tests for bivariate copulas based on likelihood depth. Computational Statistics and Data Analysis, vol. 55, pages 2724-2738, 2011.
  • Ch.H. Müller. Data depth for simple orthogonal regression with application to crack orientation. Metrika, vol. 74, pages 135-165, 2011.
  • Ch.H. Müller, C. Gunkel and L. Denecke. Statistical analysis of damage evolution with a new image tool. Fatigue & Fracture of Engineering Materials & Structures, vol. 34, pages 510-520, 2011.
  • Ch.H. Müller, R. Huggins and W.-H. Hwang. Consistent estimation of species abundance from a presence-absence map. Statistics and Probability Letters, vol. 81, pages 1449-1457, 2011.

2010

  • Ch.H. Müller and Ch Schäfer. mODa 9 - Advances in Model-Oriented Design and Analysis, chapter Designs with high breakdown point in nonlinear models, pages 137-144. Physica-Verlag, Heidelberg, 2010.
  • R. Wellmann and Ch.H. Müller. Depth notions for orthogonal regression. Journal of Multivariate Analysis, vol. 101, pages 2358-2371, 2010.
  • R. Wellmann and Ch.H. Müller. Tests for multiple regression based on simplicial depth. Journal of Multivariate Analysis, vol. 101, pages 824-838, 2010.

2009

  • A. Siudak, E. von Lieres and Ch.H. Müller. Estimation, model discrimination, and experimental design for implicitly given nonlinear models of enzyme catalyzed chemical reactions. Mathematica Slovaca, vol. 59, pages 593-610, 2009.
  • R. Wellmann, P. Harmand and Ch.H. Müller. Distribution-free tests for polynomial regression based on simplicial depth. Journal of Multivariate Analysis, vol. 100, pages 622-635, 2009.

2008

  • St. Katina, R. Wellmann and Ch.H. Müller. Simplicial depth estimators and tests in examples from shape analysis. Tatra Mt. Math. Publ., vol. 39, pages 95-104, 2008.

2007

  • Y. Fathy and Ch.H Müller. mODa 8 - Advances in Model-Oriented Design and Analysis, chapter Bayes estimators of covariance parameters and the influence of designs, pages 49-56. Physica-Verlag, Heidelberg, 2007.
  • T. Garlipp and Ch.H. Müller. Robust jump detection in regression surface. Sankhya, vol. 69, pages 55-86, 2007.
  • M. Hillebrand and Ch.H. Müller. Outlier robust corner-preserving methods for reconstructing noisy images. Ann. Statist., vol. 35, pages 132-165, 2007.
  • R. Wellmann, St. Katina and Ch.H. Müller. Calculation of simplicial depth estimators for polynomial regression with applications. Computational Statistics and Data Analysis, vol. 51, pages 5025-5040, 2007.

2006

  • T. Garlipp and Ch.H. Müller. Detection of linear and circular shapes in image analysis. Computational Statistics and Data Analysis, vol. 51, pages 1479-1490, 2006.
  • M. Hillebrand and Ch.H. Müller. On consistency of redescending M-kernel smoothers. Metrika, vol. 63, pages 71 - 90, 2006.

2005

  • T. Garlipp and Ch.H. Müller. Innovations in Classification, Data Science, and Information Systems, chapter Regression clustering with redescending M-estimators, pages 38-45. Springer-Verlag, Heidelberg, 2005.
  • Ch.H. Müller. Depth estimators and tests based on the likelihood principle with application to regression. Journal of Multivariate Analysis, vol. 95, pages 153-181, 2005.
  • Ch.H. Müller and T. Garlipp. Simple consistent cluster methods based on redescending M-estimators with an application to edge identification in images. Journal of Multivariate Analysis, vol. 92, pages 359-385, 2005.

2004

  • I. Mizera and Ch.H. Müller. Location-scale depth. Journal of the American Statistical Association, vol. 99, 2004.
  • Ch.H. Müller. Redescending M-estimators in regression analysis, cluster analysis and image analysis. Discussiones Mathematicae - Probability and Statistics, vol. 24, pages 59-75, 2004.
  • Ch.H. Müller and C.P. Kitsos. mODa 7 - Advances in Model-Oriented Design and Analysis, chapter Optimal design criteria based on tolerance regions, pages 107-115. Physica-Verlag, Heidelberg, 2004.

2003

  • Ch.H. Müller. Developments in Robust Statistics, chapter Robust estimators for estimating discontinuous functions, pages 266-276. Physica-Verlag, Heidelberg, 2003.
  • Ch.H. Müller and N. Neykov. Breakdown points of trimmed likelihood estimators and related estimators in generalized linear models. J. Statist. Plann. Inference., vol. 116, pages 503-519, 2003.
  • N. Neykov and Ch.H. Müller. Developments in Robust Statistics, chapter Breakdown point and computation of trimmed likelihood estimators in generalized linear models, pages 277-286. Physica-Verlag, Heidelberg, 2003.

2002

  • I. Mizera and Ch.H. Müller. Breakdown points of Cauchy regression-scale estimators. Statist. & Probab. Letters, vol. 57, pages 79-89, 2002.
  • Ch.H. Müller. Comparison of high breakdown point estimators for image denoising. Allg. Stat. Archiv, vol. 86, pages 307-321, 2002.
  • Ch.H. Müller. Robust estimators for estimating discontinuous functions. Metrika, vol. 55, pages 99-109, 2002.

2001

  • T. Bednarski and Ch.H. Müller. Optimal bounded influence regression and scale M-estimators. Statistics, vol. 35, pages 349-369, 2001.
  • I. Mizera and Ch.H. Müller. MODA 6 - Advances in Model-Oriented Design and Analysis, chapter The influence of the design on the breakdown point of l1-type M-estimators, pages 193-200. Physica-Verlag, Heidelberg, 2001.
  • Ch.H. Müller. Trimmed likelihood estimators in generalized linear models. In H. RiederMinsk S. Aivazian, Y. Kharin, editors, Proceedings of the Sixth International Conference on Computer Data Analysis and Modeling, pages 142-150, 2001.
  • Ch.H. Müller and St. Uhlig. Estimation of variance components with high breakdown point and high efficiency. Biometrika, vol. 88, pages 353-366, 2001.

2000

  • Ch.H. Müller. Asymptotic normality and efficiency of variance components estimators with high breakdown points. Discussiones Mathematicae - Algebra and Stochastic Methods, vol. 20, pages 85-95, 2000.

1999

  • R. Herwig, A.J. Poustka, Ch.H. Müller, Ch. Bull, H. Lehrach and J. O'Brien. Large-scale clustering of cDNA-fingerprinting data. Genome Research, vol. 9, pages 1093-1105, 1999.
  • I. Mizera and Ch.H. Müller. Breakdown points and variation exponents of robust M-estimators in linear models. Ann. Statist., vol. 27, pages 1164-1177, 1999.
  • Ch.H Müller. On the use of high breakdown point estimators in the image analysis. Tatra Mountains Math. Publ., vol. 17, pages 283-293, 1999.
  • Ch.H. Müller. Proceedings of the 52nd Session of the International Statistical Institute, chapter Bayesian designs versus maximin efficient designs for nonlinear problems, pages 145-148. Edita Ltd, Helsinki, 1999.

1998

  • Ch.H. Müller. MODA 5 - Advances in Model-Oriented Data Analysis and Experimental Design, chapter Breakdown points of estimators for aspects of linear models, pages 137-144. Physica-Verlag, Heidelberg, 1998.
  • Ch.H. Müller. Optimum robust testing in linear models. Ann. Statist., vol. 26, pages 1126-1146, 1998.
  • Ch.H. Müller and A. Pazman. Applications of necessary and sufficient conditions for maximin efficient designs. Metrika, vol. 48, pages 1-19, 1998.

1997

  • Ch.H. Müller. L1-Statistical Procedures and Related Topics, chapter L1-tests in linear models: Tests with maximum relative power, pages 91-99. Number 31 in IMS Lecture Notes. Hayward, 1997.
  • Ch.H. Müller. Industrial Statistics. Aims and Computational Aspects, chapter Robust inference and experimental design for multi-factor models, pages 165-174. Physica-Verlag, Heidelberg, 1997.
  • Ch.H. Müller. Robust Planning and Analysis of Experiments. Number 124 in Lecture Notes in Statistics. Springer, New York, 1997.

1996

  • Ch.H. Müller. COMPSTAT'96, Proceedings in Computational Statistics, chapter Computing high breakdown point estimators for planned experiments and for models with qualitative factors, pages 379-384. Physica-Verlag, 1996.
  • Ch.H. Müller. Diskussionsbeitrag zu den Aufsätzen von Plummer und Clayton sowie von Festing und Lovell. J.. Roy. Statist. Soc. Ser. B, vol. 58, page 148, 1996.
  • Ch.H. Müller. Optimal breakdown point maximizing designs. Tatra Mountains Math. Publ., vol. 7, pages 79-85, 1996.
  • Ch.H. Müller. Robust Statistics, Data Analysis, and Computer Intensive Methods - In Honor of Peter Huber's 60th Birthday, chapter High breakdown point designs, pages 353-360. Number 109 in Lecture Notes in Statistics. Springer, New York, 1996.

1995

  • C.P. Kitsos and Ch.H Müller. Robust linear calibration. Statistics, vol. 27, pages 93-106, 1995.
  • C.P. Kitsos and Ch.H. Müller. In MODA 4 - Advances in Model-Oriented Data Analysis, chapter Robust estimation of non-linear aspects, pages 223-233. Physica-Verlag, Heidelberg, 1995.
  • Ch.H. Müller. Optimal breakdown point maximizing designs. Metrika, vol. 42, pages 244-245, 1995.
  • Ch.H. Müller. Maximin efficient designs for estimating nonlinear aspects in linear models. J. Statist. Plann. Inference, vol. 44, pages 117-132, 1995.
  • Ch.H. Müller. Outlier Robust Inference for Planned Experiments. habilitation, Freie Universität Berlin, 1995.
  • Ch.H. Müller. Breakdown points for designed experiments. J. Statist. Plann. Inference., vol. 45, pages 413-427, 1995.

1994

  • Ch.H. Müller. COMPSTAT'94, Proceedings in Computational Statistics, chapter Optimal bias bounds for robust estimation in linear models, pages 257-262. Physica-Verlag, Heidelberg, 1994.
  • Ch.H. Müller. Proceedings of the International Conference on Linear Statistical Inference LINSTAT'93, chapter Optimal bias bounds for robust estimation in linear models, pages 97-102. Kluwer Academic Publishers, Dordrecht, 1994.
  • Ch.H. Müller. Asymptotic Statistics, chapter Asymptotic behaviour of one-step-M-estimators in contaminated non-linear models, pages 395-404. Physica-Verlag, Heidelberg, 1994.
  • Ch.H. Müller. Optimal designs for robust estimation in conditionally contaminated linear models. J. Statist. Plann. Inference., vol. 38, pages 125-140, 1994.
  • Ch.H. Müller. One-step-M-estimators in conditionally contaminated linear models. Stat. Decis., vol. 12, pages 331-342, 1994.

1993

  • Ch.H. Müller. Model-Oriented Data Analysis, chapter Behaviour of asymptotically optimal designs for robust estimation at finite sample sizes, pages 53-62. Physica-Verlag, Heidelberg, 1993.

1992

  • V. Kurotschka and Ch.H. Müller. Optimum robust estimation of linear aspects in conditionally contaminated linear models. Ann. Statist., vol. 20, pages 331-350, 1992.
  • Ch.H. Müller. Robust estimation with minimum bias and A-optimal designs. In J. Volaufova A. Pazman, editors, PROBASTAT'91, Proceedings of the International Conference on Probability and Mathematical Statistics, pages 109-115, 1992.
  • Ch.H. Müller. L1-Statistical Analysis and Related Methods, chapter L1-estimation and testing in conditionally contaminated linear models, pages 69-76. North-Holland, Amsterdam, 1992.

1987

  • Ch.H. Müller. Optimale Versuchspläne für robuste Schätzfunktionen in linearen Modellen. PhD thesis, Freie Universit\ät Berlin, 1987.