Rechnerorientierte Statistik und Datenanalyse

  1. Universität
  2. Fakultäten
  3. Mathematisch-Naturwissenschaftlich-Technische Fakultät
  4. Institut für Mathematik
  5. Lehrstühle
  6. Rechnerorientierte Statistik und Datenanalyse
  7. Arbeitsgruppe
  8. Prof. Dr. Gernot Müller

Prof. Dr. Gernot Müller

Ordinarius
Rechnerorientierte Statistik und Datenanalyse
Telefon: +49 821 598 - 2236
Fax: +49 821 598 - 2286
E-Mail: gernot.mueller@uni-a.de
Raum: 3029 (L1)
Sprechzeiten: per E-Mail oder nach Vereinbarung
Adresse: Universitätsstraße 14, 86159 Augsburg

Weitere Kontaktdaten

Teamassistenz

zusätzlich können Sie sich jederzeit an unsere Teamassistentin wenden

Publikationen

40

Fasching, J., Müller, G. (2022).
Day-Ahead Probabilistic Electricity Price Forecast on the German EPEX using Renewable Energy Forecast.
Preprint, Augsburg University.

39

Stemmer, B., Schiele, S., Müller, G., Trnovec, B., Sommer, B., Shiban, E., Heidecke, V. (2022).
Clinical Criteria for the Assessment of a Permanent Shunting after Endovascularly Treated Aneurysmal Subarachnoid Haemorrhage: EROS-Score.
Preprint, University Hospital Augsburg and Augsburg University.

38

Buchmann, B., Müller, G. (2022).
Time-Varying Nearly Alpha-Stable Additive Processes and their Application to Bitcoin and other Cryptocurrencies.
Preprint, Australian National University and Augsburg University.

 

36

 Lingohr, D., Müller, G. (2022).
Continuous-time Threshold Autoregressions with Jumps: Properties, Estimation, and Application to Electricity Markets.
Scandinavian Journal of Statistics, doi.org/10.1111/sjos.12597

30

 Lingohr, D., Müller, G. (2021).
Conditionally Independent Increment Processes for Modeling Electricity Prices with Regard to Renewable Power Generation.
Energy Economics 103 105244, doi.org/10.1016/j.eneco.2021.105244.

29

 Buchmann, B., Müller, G. (2021).
Changing Structures at Electricity Markets: Modelling Spot Prices using Time-Varying Stable CARMA Models.
Journal of Econometrics and Statistics 1 (2) 121-133.

26

 Müller, G., Uhl, S. (2021).
Estimation of Time-Varying Autoregressive Stochastic Volatility Models with Stable Innovations.
Statistics and Computing 31 36.

22

 

 Seibert, A., Sirchenko, A., Müller, G. (2021).
A Model for Policy Interest Rates.
Journal of Economic Dynamics and Control 124 104049.

21

 Lingohr, D., Müller, G. (2019).
Stochastic Modelling of Intraday Photovoltaic Power Generation.
Energy Economics 81 175-186.

20

 

 

 Müller, G., Seibert, A. (2019).
Bayesian Estimation of Stable CARMA Spot Models for Electricity Prices.
Energy Economics 78 267-277.

19

 

 

 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.

18

 

 

 Jacod, J., Klüppelberg, C., Müller, G. (2017).
Testing for Non-Correlation Between Price and Volatility Jumps.
Journal of Econometrics 197 (2) 284-297.

17

 

 

 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.

16

 

 

 Buchmann, B., Müller, G. (2012).
Limit Experiments of GARCH.
Bernoulli 18 (1) 64-99.

15

 

 

 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.

14

 

 

 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.

13

 

 

 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.

12

 

 

 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.

11

 

 

 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.

10

 

 

 Müller, G. (2010).
MCMC Estimation of the COGARCH(1,1) Model.
Journal of Financial Econometrics 8 (4) 481-510.

9

 

 

 

 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.

8

 

 

 

 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.

7

 

 

 

 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.

5

 

 

 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.

4

 

 

 Müller, G., Czado, C. (2009).
Stochastic Volatility Models for Ordinal Valued Time Series with Application to Finance.
Statistical Modelling 9 (1) 69-95.

3

 

 

 

 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.

2

 

 

 Maller, R. A., Müller, G., Szimayer, A. (2008).
GARCH Modelling in Continuous Time for Irregularly Spaced Time Series Data.
Bernoulli 14 (2) 519-542.

1

 

 

 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.

 

37

Schrempf M.C., Petzold J., Petersen M.A., Arndt T.T., Schiele S., Vachon H., Vlasenko D., Wolf S., Anthuber M., Müller G., Sommer F. (2022 Jul 14).
A randomised pilot trial of virtual reality-based relaxation for enhancement of perioperative well-being, mood and quality of life.
scientific reports, doi: 10.1038/s41598-022-16270-8; PMID: 35835944; PMCID: PMC9282619.

35

Filippini Velázquez G., Schiele S., Gerken M., Neumaier S., Hackl C., Mayr P., Klinkhammer-Schalke M., Illerhaus G., Schlitt H.J., Anthuber M., Kröncke T., Messmann H., Märkl B., Schmid C., Trepel M., Müller G., Claus R., Hackanson B. (2022).
Predictive preoperative clinical score for patients with liver-only oligometastatic colorectal cancer.
ESMO Open, 7 (3), 100470, doi.org/10.1016/j.esmoop.2022.100470

34

Jering, M., Mayer, M., Thölken, R., Schiele, S., Müller, G., Zenk, J. (2022).

Cancer-Specific and Overall Survival of Patients with Primary and Metastatic Malignancies of the Parotid Gland - A Retrospective Study.

Journal of Cranio-Maxillofacial Surgery, doi.org/10.1016/j.jcms.2022.03.001

33

 Epple, T., Friedmann, A., Wetzel, K.-F., Born, O., Müller, G. (2022).
The Migration of Four Salmonid Species Through Fish-Bypass Channels Depending on Environmental Factors.

Environmental Biology of Fishes, doi.org/10.1007/s10641-022-01233-9

32

 Waidhauser, J., Nerlinger, P., Arndt, T., Schiele, S., Sommer, F., Wolf, S., Löhr, P., Eser, S., Müller, G., Claus, R., Märkl, B., Rank, A. (2021).
Alterations of Circulating Lymphocyte Subsets in Patients with Colorectal Carcinoma.
Cancer Immunology, Immunotherapy  doi.org/10.1007/s00262-021-03127-8

31

 Thölken, R., Jering, M., Mayer, M., Schiele, S., Müller, G., Zenk, J. (2021).
Prospective Study on Complications using Different Techniques for Parotidectomy for Benign Tumors.
Laryngoscope Investigative Otolaryngology 2021 1-9 doi.org/10.1002/lio2.694

28

 Martin, B., Grosser, B., Kempkens, L., Miller, S., Bauer, S., Dhillon, C., Banner, B. M., Brendel, E.-M., Sipos, É., Vlasenko, D., Schenkirsch, G., Schiele, S., Müller, G., Märkl, B. (2021).
Stroma AReactive Invasion Front Areas (SARIFA) – a New Easily to Determine Biomarker in Colon Cancer – Results of a Retrospective Study.
Cancers, 13 (19), 4880; doi.org/10.3390/cancers13194880

27

Glückstein, M.-I., Dintner, S., Arndt, T., Vlasenko, D., Schenkirsch, G., Agaimy, A., Müller, G., Märkl, B., Grosser, B. (2021).
Comprehensive Immunohistochemical Study of the SWI/SNF Complex Expression Status in Gastric Cancer Reveals an Adverse Prognosis of SWI/SNF Deficiency in Genomically Stable Gastric Carcinomas.
Cancers, 13 (15), 3894; doi.org/10.3390/cancers13153894

25

Hirschbühl, K., Dintner, S., Beer, M., Wylezich, C., Schlegel, J., Delbridge, C., Borcherding, L., Lippert, J., Schiele, S., Müller, G., Moiraki, D., Spring, O., Wittmann, M., Kling, E., Braun, G., Kröncke, T., Claus, R., Märkl, B., Schaller, T. (2021).
Viral Mapping in COVID-19 Deceased in the Augsburg Autopsy Series of the First Wave: A Multiorgan and Multimethodological Approach.
PLoS ONE 16 (7) e0254872.

24

 

 

 Löhr, P., Schiele, S., Arndt, T., Grützner, S., Claus, R., Römmele, C., Müller, G., Schmid, C., Dennehy, K.M., Rank, A. (2021).
Impact of Age and Gender on Lymphocyte Subset Counts in Patients with COVID-19.
Cytometry Part A, doi.org/10.1002/cyto.a.24470.

23

 

 Schiele, S., Arndt, T., Martin, B., Miller, S., Bauer, S., Banner, B., Brendel, E.-M., Schenkirsch, G., Anthuber, M., Huss, R., Märkl, B., Müller, G. (2021).
Deep Learning Prediction of Metastasis in Locally Advanced Colon Cancer using Binary Histologic Tumor Images.
Cancers 13 (9) 2074.

6

 

 

 Czado, C., Heyn, A., Müller, G. (2010).
Modeling Individual Migraine Severity with Autoregressive Ordered Probit Models.
Statistical Methods and Applications 20 (1) 101-121.

 

  • Die Flut der Daten bewältigen (Interview, Augsburger Allgemeine Zeitung vom 30.07.2022, Seite 14)

  • 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

  • Artificial Intelligence
  • Bayesian Statistics
  • Computational Econometrics
  • Data Analysis
  • Energy Economics
  • Statistics in Medicine
 
 

Spezialvorlesungen

  • Advanced Methods in Machine Learning (Teile I und II)
  • Bayessche Statistik
  • Generalisierte Lineare Modelle (mit Anwendungen in Finance and Insurance)
  • Stochastische Modelle für Energiemärkte
 
 

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

Mitgliedschaften

Gewähltes Mitglied in

  • International Statistical Institute (ISI)

 

Mitglied in

  • Bernoulli Society (BSMSP)
  • Deutsche Mathematiker-Vereinigung (DMV)
  • Deutscher Hochschulverband (DHV)>
  • International Society for Bayesian Analysis (ISBA)

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