Lossless Transformations and Excess Risk Bounds in Statistical Inference

Lossless Transformations and Excess Risk Bounds in Statistical Inference

We study the excess minimum risk in statistical inference, defined as the difference between the minimum expected loss when estimating a random variable from an observed feature vector and the minimum expected loss when estimating the same random variable from a transformation (statistic) of the fea...

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Bibliographic Details
Main Authors: László Györfi, Tamás Linder, Harro Walk
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Entropy
Subjects:
statistical inference with loss
strongly consistent test
information-theoretic bounds
classification
regression
portfolio selection
Online Access:https://www.mdpi.com/1099-4300/25/10/1394

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https://www.mdpi.com/1099-4300/25/10/1394

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