[Statlist] Reminder: ETH/UZH Research Seminar by Alexander Henzi, ETH, Seminar for Statistics, 30.09.2022

Maurer Letizia |et|z|@m@urer @end|ng |rom ethz@ch
Mon Sep 26 10:30:41 CEST 2022


We are glad to announce the following talk in the ETH/UZH Research Seminar:

"Isotonic distributional regression"   
by Alexander Henzi, ETH Zurich, Seminar for Statistics

Time: Friday,  30.09.22 at 15.15 h
Place: ETH Zurich, HG G 19.1

Abstract: Statistical predictions should provide a quantification of forecast uncertainty. Ideally, this uncertainty quantification is in the form of a probability distribution for the outcome of interest conditional on the available information. Isotonic distributional regression (IDR) is a nonparametric method that allows to derive probabilistic forecasts from a training data set of point predictions and observations, solely under the assumption of stochastic monotonicity. IDR does not require parameter tuning, and it has interesting properties when analyzed under the paradigm of maximizing sharpness subject to calibration. The method can serve as a natural benchmark for postprocessing forecasts both from statistical models and external sources, which is illustrated through applications in weather forecasting and medicine.

Seminar website: https://math.ethz.ch/sfs/news-and-events/research-seminar.html

Research Seminar – Seminar for Statistics | ETH Zurich
math.ethz.ch


Organisers: A. Bandeira, P. L. Bühlmann, R. Furrer, L. Held, T. Hothorn, D. Kozbur, M. H. Maathuis, N. Meinshausen, S. van de Geer, M. Wolf




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