Isotonic recalibration under a low signal-to-noise ratio

DOI10.1080/03461238.2023.2246743arXiv2301.02692OpenAlexW4385982646MaRDI QIDQ6127100

Johanna F. Ziegel, Mario V. Wüthrich

Publication date: 10 April 2024

Published in: Scandinavian Actuarial Journal (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2301.02692

zbMATH Keywords

auto-calibrationisotonic regressiondeep neural networkexplainabilityalgorithmic solutionlow signal-to-noise ratiocross-financingisotonic recalibration

Mathematics Subject Classification ID

Actuarial mathematics (91G05)

Cites Work

• Unnamed Item
• Unnamed Item
• Making and Evaluating Point Forecasts
• Minimizing integrals in certain classes of monotone functions
• A general method for comparing probability assessors
• On the degrees of freedom in shape-restricted regression.
• Least squares estimation in the monotone single index model
• Nonmetric multidimensional scaling. A numerical method
• Autocalibration and Tweedie-dominance for insurance pricing with machine learning
• An Empirical Distribution Function for Sampling with Incomplete Information
• THE COMPLETE AMALGAMATION INTO BLOCKS, BY WEIGHTED MEANS, OF A FINITE SET OF REAL NUMBERS
• Goodness of fit tests for the multiple logistic regression model
• Local Regression and Likelihood
• Calibrating sufficiently
• Isotonic Distributional Regression
• An Introduction to Variational Autoencoders
• The Isotonic Regression Problem and Its Dual
• Elicitation of Personal Probabilities and Expectations
• Local bias adjustment, duration-weighted probabilities, and automatic construction of tariff cells
• Distributional (Single) Index Models
• Model selection with Gini indices under auto-calibration

This page was built for publication: Isotonic recalibration under a low signal-to-noise ratio