Prof. Dr. Gernot Müller
Ordinarius
Rechnerorientierte Statistik und Datenanalyse
| Telefon: | +49 821 598 - 2236 |
| Fax: | +49 821 598 - 2286 |
| E-Mail: | |
| Raum: | 3029 (L1) |
| Sprechzeiten: | per E-Mail oder nach Vereinbarung |
| Adresse: | Universitätsstraße 14, 86159 Augsburg |
Weitere Kontaktdaten
Publikationen
- Schiele, S., Martin, B., Märkl, B., Anthuber, M., Schenkirsch, G., Müller, G. (2020).
Deep Learning for Classification of Colon Cancer with Respect to 5-Year Survival.
Preprint, Augsburg University. - Martin, B., Banner, B., Anthuber, M., Schenkisch, G., Müller, G., Schiele, S., Märkl, B. (2020).
Tumor Proportion in Colon Cancer – Results from a Semiautomatic Image Analysis.
Preprint, Augsburg University. - Lingohr, D., Müller, G. (2020).
Conditionally Independent Increment Processes for Modeling Electricity Prices with Regard to Renewable Power Generation.
Preprint, Augsburg University. - Stemmer, B., Schiele, S., Müller, G., Trnovec, B.; Sommer, B.; Shiban, E., Heidecke, V. (2020).
Clinical criteria for the assessment of a permanent shunting after endovascularly treated aneurysmal subarachnoid haemorrhage: EROS-Score.
Preprint, University Hospital Augsburg and Augsburg University.
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Schiele, S., Martin, B., Märkl, B., Anthuber, M., Schenkirsch, G., Müller, G. (2020). Deep Learning for Classification of Colon Cancer with Respect to 5-Year Survival. Preprint, Augsburg University. |
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Martin, B., Banner, B., Anthuber, M., Schenkisch, G., Müller, G., Schiele, S., Märkl, B. (2020). Tumor Proportion in Colon Cancer – Results from a Semiautomatic Image Analysis. Preprint, Augsburg University. |
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Lingohr, D., Müller, G. (2020). Conditionally Independent Increment Processes for Modeling Electricity Prices with Regard to Renewable Power Generation. Preprint, Augsburg University. |
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Stemmer, B., Schiele, S., Müller, G., Trnovec, B.; Sommer, B.; Shiban, E., Heidecke, V. (2020). Clinical criteria for the assessment of a permanent shunting after endovascularly treated aneurysmal subarachnoid haemorrhage: EROS-Score. Preprint, University Hospital Augsburg and Augsburg University. |
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Müller, G., Uhl, S. (2020) Time-Varying Autoregressive Models with Stochastically Scaled Stable Innovations. Preprint, Augsburg University. |
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Seibert, A., Sirchenko, A., Müller, G. (2020) Modelling Policy Interest Rates using Cross-Nested AOP Models. Preprint, Augsburg University and Higher School of Economics Moscow. |
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Buchmann, B., Müller, G. (2020) Time-Varying Nearly Alpha-Stable Additive Processes and their Application in Electricity Spot Price Modelling. Preprint, Australian National University and Augsburg University. |
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Lingohr, D., Müller, G. (2019) Stochastic Modelling of Intraday Photovoltaic Power Generation. Energy Economics 81 175-186 |
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Müller, G., Seibert, A. (2019) Bayesian Estimation of Stable CARMA Spot Models for Electricity Prices. Energy Economics 78 267-277. |
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James, L., Müller, G., Zhang, Z. (2018) Stochastic Volatility Models based on OU-Gamma Time Change: Theory and Estimation. Journal of Business and Economic Statistics 36 (1) 75-87. |
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Jacod, J., Klüppelberg, C., Müller, G. (2017) Testing for Non-Correlation Between Price and Volatility Jumps. Journal of Econometrics 197 (2) 284-297. |
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Benth, F.E., Klüppelberg, C., Müller, G., Vos, L. (2014) Futures Pricing in Electricity Markets Based on Stable CARMA Spot Models. Energy Economics 44 392–406. |
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Buchmann, B., Müller, G. (2012) Limit Experiments of GARCH. Bernoulli 18 (1) 64-99. |
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Jacod, J., Klüppelberg, C., Müller, G. (2012) Functional Relationships Between Price and Volatility Jumps and Their Consequences for Discretely Observed Data. Journal of Applied Probability 49 (4) 901-914. |
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Schreiber, I., Müller, G., Klüppelberg, C., Wagner, N. (2012) Equities, Credits and Volatilities: A Multivariate Analysis of the European Market During the Sub-prime Crisis. International Review of Financial Analysis 24 (C) 57-65. |
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Müller, G., Durand, R. B., Maller, R. A. (2011) The Risk Return Tradeoff: A COGARCH Analysis of Merton's Hypothesis. Journal of Empirical Finance 18 (2) 306-320. |
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Fleischer, P., Maller, R. A., Müller, G. (2011) A Bayesian Analysis of Market Information Linkages among NAFTA Countries using a Multivariate SV Model. Journal of Economics and Finance 35 (2) 123-148. |
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García, I., Klüppelberg, C., Müller, G. (2011) Estimation of Stable CARMA Models with an Application to Electricity Spot Prices. Statistical Modelling 11 (5) 447-470. |
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Müller, G. (2010) MCMC Estimation of the COGARCH(1,1) Model. Journal of Financial Econometrics 8 (4) 481-510. |
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Müller, G. (2010) Market Correlations in the Euro Changeover Period With a View to Portfolio Management. In: Böcker, K. (Ed.) Rethinking Risk Measurement and Reporting: Uncertainty, Bayesian Analysis and Expert Judgement, Vol. I. Risk Books, London, pp. 107-125. |
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Gebhard, Ph., Müller, G., Böcker, K. (2010) Bayesian Estimation of Lévy Copulas for Multivariate Operational Risks. In: Böcker, K. (Ed.) Rethinking Risk Measurement and Reporting: Uncertainty, Bayesian Analysis and Expert Judgement, Vol. II. Risk Books, London, pp. 439-463. |
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Czado, C., Müller, G., Nguyen, T. (2010) Ordinal- and Continuous-response SV Models for Price Changes: An Empirical Comparison. In: Kneib, T., Tutz, G. (Eds.) Statistical Modelling and Regression Structures - Festschrift in Honour of Ludwig Fahrmeir. Springer, Berlin, pp. 301-320. |
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Czado, C., Heyn, A., Müller, G. (2010) Modeling Individual Migraine Severity with Autoregressive Ordered Probit Models. Statistical Methods and Applications 20 (1) 101-121. |
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Müller, G., Durand, R. B., Maller, R. A., Klüppelberg, C. (2009) Analysis of Stock Market Volatility by Continuous-time GARCH models. In: Gregoriou, G.N. (Ed.) Stock Market Volatility. Chapman and Hall-CRC/Taylor and Francis, London, pp. 31-50. |
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Müller, G., Czado, C. (2009) Stochastic Volatility Models for Ordinal Valued Time Series with Application to Finance. Statistical Modelling 9 (1) 69-95. |
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Maller, R. A., Müller, G., Szimayer, A. (2009) Ornstein-Uhlenbeck Processes and Extensions. In: Andersen, T. G., Davis, R. A., Kreiß, J.-P., Mikosch, Th. (Eds.) Handbook of Financial Time Series. Springer, Berlin, pp. 421-437. |
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Maller, R. A., Müller, G., Szimayer, A. (2008) GARCH Modelling in Continuous Time for Irregularly Spaced Time Series Data. Bernoulli 14 (2) 519-542. |
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Müller, G., Czado, C. (2005) An Autoregressive Ordered Probit Model with Application to High-Frequency Finance. Journal of Computational and Graphical Statistics 14 (2) 320-338. |
- Corona und die Macht des Zufalls (Augsburger Allgemeine Zeitung vom 20.04.2020, Seite 4)
- Interview zum Klimawandel (für SBS Radio Australia, Sydney, 20.12.2019)
- Wahlbetrug und Steuerhinterziehung: Kriminalistik mit Statistik (Open-Science-Vortrag, seit 2017)
- Die verborgenen Strukturen des Zufalls (Open-Science-Vortrag, seit 2016)
- Mit Bits und Bytes dem Zufall auf der Spur (Open-Science-Vortrag, seit 2015)
- Maller, R. A., Müller, G. (2010)
On the Residuals of GARCH(1,1) and Extensions when Estimated by Maximum Likelihood.
Technical Report, Australian National University and Technische Universität München. - Müller, G., Czado, C. (2006)
Stochastic Volatility Models for Ordinal Valued Time Series with Application to Finance.
SFB 386 „Statistische Analyse diskreter Strukturen”, Discussion Paper 504, Technische Universität München. - Czado, C., Heyn, A., Müller, G. (2005)
Modeling Migraine Severity with Autoregressive Ordered Probit Models.
SFB 386 „Statistische Analyse diskreter Strukturen”, Discussion Paper 463, Technische Universität München. - Müller, G., Czado, C., Antes, S., Rottenwallner, M. (2003)
Regression Models for Ordinal Valued Time Series: Applications in High Frequency Finance and Medicine.
SFB 386 „Statistische Analyse diskreter Strukturen”, Discussion Paper 335, Technische Universität München. - Müller, G., Czado, C. (2002)
Regression Models for Ordinal Valued Time Series with Application to High Frequency Financial Data.
SFB 386 „Statistische Analyse diskreter Strukturen”, Discussion Paper 301, Technische Universität München.
- Müller, G. (2010)
Statistical Methods for Time Series Analysis in Finance, Insurance and Electricity.
Habilitation Thesis, Technische Universität München - Müller, G. (2004)
Regression Models for Ordinal Valued Time Series: Estimation and Applications in Finance.
PhD Thesis, Technische Universität München - Müller, G. (2000)
Vorhersage bei Zeitreihen.
Diploma Thesis, Julius-Maximilians-Universität Würzburg
Forschungsinteressen
- Bayesian Statistics
- Computational Econometrics
- Data Analysis
- Statistics in Medicine
Lebenslauf
Beruflicher Werdegang
| seit 08/2013 | Lehrstuhlinhaber des Lehrstuhls „Rechnerorientierte Statistik und Datenanalyse", Universität Augsburg |
| 04/2013 bis 07/2013 | Professor für Angewandte Statistik, Universität Oldenburg |
| 04/2012 bis 03/2013 | Akad. Oberrat, Zentrum Mathematik, TU München |
| 10/2011 bis 03/2012 | Vertretungsprofessor für Computationale Statistik, LMU München |
| 08/2006 bis 09/2011 | Akad. Rat / Oberrat, Zentrum Mathematik, TU München |
| 02/2006 bis 08/2006 |
Research Fellow, School of Finance and Applied Statistics und Center for Mathematics and its Applications, Australian National University, Canberra, Australien |
| 10/2000 bis 02/2006 | Wissenschaftlicher Mitarbeiter / Akad. Rat, Zentrum Mathematik, TU München |
Qualifikationen
| 2010 | Habilitation, Zentrum Mathematik, TU München |
| 2004 | Dr. rer. nat., Zentrum Mathematik, TU München |
| 2000 | Diplom Mathematik (Nebenfach Informatik), Universität Würzburg |