Shapley Curves: A Smoothing Perspective
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10507669" target="_blank" >RIV/00216208:11320/25:10507669 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=cyDLvcVp1G" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=cyDLvcVp1G</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/07350015.2024.2365781" target="_blank" >10.1080/07350015.2024.2365781</a>
Alternative languages
Result language
angličtina
Original language name
Shapley Curves: A Smoothing Perspective
Original language description
This article fills the limited statistical understanding of Shapley values as a variable importance measure from a nonparametric (or smoothing) perspective. We introduce population-level Shapley curves to measure the true variable importance, determined by the conditional expectation function and the distribution of covariates. Having defined the estimand, we derive minimax convergence rates and asymptotic normality under general conditions for the two leading estimation strategies. For finite sample inference, we propose a novel version of the wild bootstrap procedure tailored for capturing lower-order terms in the estimation of Shapley curves. Numerical studies confirm our theoretical findings, and an empirical application analyzes the determining factors of vehicle prices.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GX19-28231X" target="_blank" >GX19-28231X: DyMoDiF - Dynamic Models for the Digital Finance</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Business and Economic Statistics
ISSN
0735-0015
e-ISSN
1537-2707
Volume of the periodical
43
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
12
Pages from-to
312-323
UT code for WoS article
001314392800001
EID of the result in the Scopus database
2-s2.0-105001083802