Prof. Dr. Wolfgang Trutschnig curriculum vitae (status 2024-09)Professor for Stochastics & Director IDA Lab SalzburgDepartment for Artificial Intelligence & Human Interfaces (AIHI) University of Salzburg Hellbrunner Strasse 34 A-5020 Salzburg Austria Tel: +43 662 8044 5326 Email: wolfgang@trutschnig.net Profiles: Google scholar Scopus Author ID: 25652347200 ORCID: 0000-0002-7131-1944 zbMATH entry Co-Managing Director correlate analytics gmbh |
What has the average distance/dissimilarity of two randomly drawn conditional distributions to do with directed dependence - new preprint:[01] J. Ansari, P.B. Langthaler, S. Fuchs, W. Trutschnig: Quantifying and estimating dependence via sensitivity of conditional distributions, arXiv preprintNew textbook - excursion to ergodic theory:[01] J. Fernández-Sánchez, J. López-Salazar Codes, J.B. Seoane Sepúlveda, W. Trutschnig: Generalized Notions of Continued Fractions: Ergodicity and Number Theoretic Applications (1st ed.) , Chapman and Hall/CRC (2023), doi:10.1201/9781003404064Calculating and estimating the extent of multivariate (directed) dependence - new article:[47] F. Griessenberger, R.R. Junker, W. Trutschnig: On a multivariate copula-based dependence measure and its estimation, Electronic Journal of Statistics 16, 2206-2251 (2022), doi:10.1214/22-EJS2005 preprint (pdf)Why the so-called simplifying assumption is not as flexible as frequently praised - new article:[43] T. Mroz, S. Fuchs, W. Trutschnig: How simplifying and flexible is the simplifying assumption in pair-copula constructions - analytic answers in dimension three and a glimpse beyond, Electronic Journal of Statistics 15, 1951-1992 (2021), doi:10.1214/21-EJS1832 preprint (pdf) |
Research InterestsProbability Theory & Mathematical Statistics, Fractals, AnalysisCopulas and Dependence ModelsMultivariate and Nonparametric Statistics Dynamical Systems (in discrete time) and their interplay with number theory Fractals, Singular Functions and Iterated Function Systems Markov Operators and Kernels Lineability, spaceability, algebrability, latticeability Applied Statistics & Data ScienceProbabilistic fundamentals of Machine LearningForecasting and Regression Techniques Feature Selection Dependence Modeling of processes Automatic Reporting with R and Miktex (knitR, Sweave) Interactive Dashboards with shiny | | pic as pdf |
| pic as png pic as pdf (joint work with Manuela Schreyer) slides Fraktale und Zufall (Tag der Mathematik, PH-Salzburg) |