The Wasserstein impact measure (WIM): a practical tool for quantifying prior impact in Bayesian statistics

DOI10.1016/j.csda.2021.107352OpenAlexW3203752172MaRDI QIDQ2157491

Christophe Ley, Ben Serrien, Fatemeh Ghaderinezhad

Publication date: 22 July 2022

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2021.107352

zbMATH Keywords

prior distributionneutralityWasserstein distanceeffective sample sizeVallender formula

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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