Mathematical Methods of Modern Statistics 2 / Méthodes mathématiques en statistiques modernes 2

Collection Mathematical Methods of Modern Statistics 2 / Méthodes mathématiques en statistiques modernes 2

Organizer(s) Bogdan, Malgorzata ; Graczyk, Piotr ; Panloup, Fabien ; Proïa, Frédéric ; Roquain, Etienne

Date(s) 15/06/2020 - 19/06/2020

linked URL https://www.cirm-math.com/cirm-virtual-event-2146.html

00:00:00 / 00:00:00

4 25

Scaling of scoring rules

By Jonas Wallin

Averages of proper scoring rules are often used to rank probabilistic forecasts. In many cases, the individual observations and their predictive distributions in these averages have variable scale (variance). I will show that some of the most popular proper scoring rules, such as the continuous ranked probability score (CRPS), up-weight observations with large uncertainty which can lead to unintuitive rankings. We have developed a new scoring rule, scaled CRPS (SCRPS), this new proper scoring rule is locally scale invariant and therefore works in the case of varying uncertainty. I will demonstrate this how this affects model selection through parameter estimation in spatial statitics.

Information about the video

Date of recording 02/06/2020
Date of publication 15/06/2020
Institution CIRM
Licence CC BY NC ND
Language English
Audience Researchers
Director(s) Guillaume Hennenfent
Format MP4

Citation data

DOI 10.24350/CIRM.V.19644103
Cite this video Wallin, Jonas (02/06/2020). Scaling of scoring rules. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.19644103
URL https://dx.doi.org/10.24350/CIRM.V.19644103

Domain(s)

Bibliography

BOLIN, David et WALLIN, Jonas. Scale invariant proper scoring rules Scale dependence: Why the average CRPS often is inappropriate for ranking probabilistic forecasts. arXiv preprint arXiv:1912.05642, 2019. - https://arxiv.org/abs/1912.05642

MSC codes

Document(s)

https://www.cirm-math.fr/RepOrga/2146/Slides/Wallin.pdf

Last related questions on MathOverflow

You have to connect your Carmin.tv account with mathoverflow to add question

Ask a question on MathOverflow

All the collection videos

01:08:34

published on June 15, 2020

Consistent model selection criteria and goodness-of-fit test for common time series models

By Jean-Marc Bardet

01:01:17

published on June 15, 2020

Isotonic Distributional Regression (IDR) - leveraging monotonicity, uniquely so!

By Tilmann Gneiting

57:07

published on June 15, 2020

Quasi logistic distributions and Gaussian scale mixing

By Gerard Letac

35:09

published on June 15, 2020

Scaling of scoring rules

By Jonas Wallin

34:07

published on June 15, 2020

The price of competition: effect size heterogeneity matters in high dimensions!

By Hua Wang

36:40

published on June 15, 2020

How to estimate a density on a spider web ?

By Dominique Picard

39:06

published on June 15, 2020

High-dimensional classification by sparse logistic regression

By Felix Abramovich

38:07

published on June 15, 2020

Optimal control of false discovery criteria in the general two-group model

By Ruth Heller

32:25

published on June 15, 2020

Sparse multiple testing: can one estimate the null distribution ?

By Etienne Roquain

50:46

published on June 15, 2020

Hierarchical bayes modeling for large-scale inference

By Daniel Yekutieli

29:01

published on June 15, 2020

On Cholesky structures on real symmetric matrices and their applications

By Hideyuki Ishi

29:04

published on June 15, 2020

Treatment effect estimation with missing attributes

By Julie Josse

56:18

published on June 15, 2020

Knockoff genotypes: value in counterfeit

By Chiara Sabatti

50:05

published on June 15, 2020

The smoothed multivariate square-root Lasso: an optimization lens on concomitant estimation

By Joseph Salmon

39:43

published on June 15, 2020

High-dimensional, multiscale online changepoint detection

By Richard Samworth

46:32

published on June 15, 2020

De-biasing arbitrary convex regularizers and asymptotic normality

By Pierre C. Bellec

48:44

published on June 15, 2020

Floodgate: inference for model-free variable importance

By Lucas Janson

15:53

published on June 15, 2020

Shrinkage estimation of mean for complex multivariate normal distribution with unknown covariance when p > n

By Yoshihiko Konno

42:35

published on June 15, 2020

Structure learning for CTBN's

By Błażej Miasojedow

34:30

published on June 15, 2020

Universal inference using the split likelihood ratio test

By Aaditya K. Ramdas

46:04

published on June 15, 2020

Optimal and maximin procedures for multiple testing problems

By Saharon Rosset

34:46

published on June 15, 2020

Post hoc bounds on false positives using reference families

By Pierre Neuvial

38:00

published on June 15, 2020

Change: detection, estimation, segmentation

By David Siegmund

32:29

published on June 15, 2020

Bayesian spatial adaptation

By Veronika Rockova

54:34

published on June 15, 2020

Experimenting in equilibrium

By Stefan Wager

Copyright Carmin.tv 2024

Give feedback