dr. (Andreas) A Alfons

Erasmus School of Economics

Associate professor | Econometrics
Email
alfons@ese.eur.nl

Work

  • Savannah Boele, Natalie Terzikhan, Maarten Boksem, Wendy van de Sande, Silvan Licher & Andreas Alfons (27 oktober 2023) - CollectieveKracht takes home Open and Responsible Science award

  • Andreas Alfons (2024) - International Conference on Robust Statistics and Data Science, Statistics & Visualisation
  • Kathrin Gruber, Andreas Alfons, Achim Zeileis, Caroline Strobl & Florian Wickelmaier (2024) - International Workshop on Psychometric Computing
  • Andreas Alfons (2024) - Journal of Data Science, Statistics and Visualisation (Journal)
  • Andreas Alfons (2023) - International Conference on Robust Statistics
  • Andreas Alfons (2023) - Journal of Statistical Software (Journal)
  • Andreas Alfons (2022) - International Conference of the ERCIM WG on Computational and Methodological Statistics
  • Andreas Alfons, Patrick Groenen, Mark de Rooij, Carlo Cavicchia, Mikhail Zhelonkin & Max Welz (2021) - Data Science, Statistics & Visualisation and European Conference on Data Analysis
  • Andreas Alfons & Mikhail Zhelonkin (2018) - Econometric Institute Workshop: Robust Statistics
  • Andreas Alfons & Rainer St├╝tz (2016) - Austrian Journal of Statistics (Journal)

  • Andreas Alfons (2022) - ERIM Open Science Award
  • MFO (Max) Welz, A (Andreas) Alfons & K. (Kevin) ten Haaf (2021) - Open Mind Call 2021 Health and Technology
  • A (Andreas) Alfons (2018) - NWO Vidi: Robust analysis of (big) rating-scale data in the social sciences
  • Andreas Alfons (2017) - ESE Top Talent Researcher Award

Thesis Hub Master Economics & Business

Year
2023
Course Code
FEM61007

Internship Hub

Year
2023
Course Code
FEB63017

Machine Learning in Finance

Year
2023
Course Code
FEM21045

Machine Learning

Level
master
Year Level
master
Year
2023
Course Code
FEM31002

  • Gertjan van den Burg

    Algorithms for Multiclass Classification and Regularized Regression
  • Max Felix Orson Welz

    Robustifying the Analysis of Big Rating-Scale Data Against Outliers

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