Regressing on distributions in panel models: The nonlinear effect of temperature on regional economic growth A framework is proposed for the situation where certain explanatory variables are available at a higher temporal resolution than the dependent variable. The main idea is to use the moments of the empirical distribution of these variables to construct regressors […]
Statistical process monitoring of artificial neural networks The rapid advancement of models based on artificial intelligence demands innovative monitoring techniques which can operate in real time with low computational costs. In machine learning, especially if we consider artificial neural networks (ANN), the models are often trained in a supervised manner. Consequently, the learned relationship between […]
Über "magische Steine" in der Statistik Auf Charles Stein geht die Idee zurück, parametrische Verteilungsfamilien auf eindeutige Weise durch eine auf Momenten basierende Identität zu charakterisieren, wobei eine solche Identität von einer unbestimmten Funktion f abhängt, welche aus einer großen Klasse von Funktionen frei wählbar ist. Ursprünglich wurde dieser Ansatz dabei im Rahmen der Wahrscheinlichkeitstheorie […]
Optimale Portfolios in einem Finanzmarkt mit Gaußscher Drift und Expertenmeinungen Wir untersuchen optimale Portfoliostrategien für nutzenmaximierende Investoren in einem zeitstetigen Finanzmarktmodell, bei dem die Driftdurch einen Ornstein-Uhlenbeck-Prozess modelliert wird, welcher nicht direkt beobachtbar und vom Investor aus den ihm zur Verfügung stehenden Information zu schätzen ist. In der Praxis beziehen Investoren für die Bestimmung ihrer […]
Ordinal patterns: Different representations and their application in the context of dependence Since the seminal paper by Bandt and Pompe, so called ordinal patterns have been used extensively in contexts of data analysis, dynamical systems as well as time series analysis and mathematical statistics. Ordinal patterns are defined as the description of the order of […]
Goodness-of-fit testing for INAR models In recent years, there has been a growing interest in the analysis of time series of counts. Among the various models designed for dependent count data, integer-valued autoregressive (INAR) processes enjoy great popularity. These processes serve as a natural extension of the widely known AR model used in the context […]
Dependence, examples and tools The talk first aims at recalling some basic facts linking independence and orthogonality structures. This will mange to provide simple conditions to model stochastic dependences. Some other simple features will also suggest a definition of weak proposed in a paper of 1999 with Sana Louhichi which has some advantages with respect […]
Statistical Approaches to Harmonization in Multi-Center Medical Imaging Studies While magnetic resonance imaging (MRI) studies are critical for the diagnosis, monitoring, and study of a wide variety of diseases, their use in quantitative analysis can be complex. An increasingly recognized issue involves the differences between MRI scanners that are used in large multi-center studies. To […]
Testing for Dependence by Using Ordinal Patterns: an Introduction About 20 years ago, ordinal patterns have been introduced as a simple, robust, and flexible tool for analyzing the serial dependence structure of univariate real-valued stochastic processes. If applied to continuously distributed processes, one can derive non-parametric tests of the null hypothesis that the process is […]
Analysis of Hydroacoustical Time Series by State Space Modelling This talk deals with predictive time-domain modelling of time series, either univariate or multivariate. The aim is to identify and reconstruct independent source components from the time series. For this purpose, a special class of linear state space models is employed, which describes the individual source […]