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The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions
A popular rule of thumb, usually called “heuristic technique” in Behavioral Economics, for determining the likelihood insensitivity regions of probability weighting functions (pwf’s) is based on searching for points at which the pwf’s are twice their values at half the points. Although this techniqu...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8972790/ https://www.ncbi.nlm.nih.gov/pubmed/35382141 http://dx.doi.org/10.1007/s10614-022-10252-8 |
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author | Egozcue, Martín García, Luis Fuentes Zitikis, Ričardas |
author_facet | Egozcue, Martín García, Luis Fuentes Zitikis, Ričardas |
author_sort | Egozcue, Martín |
collection | PubMed |
description | A popular rule of thumb, usually called “heuristic technique” in Behavioral Economics, for determining the likelihood insensitivity regions of probability weighting functions (pwf’s) is based on searching for points at which the pwf’s are twice their values at half the points. Although this technique works remarkably well for many commonly used pwf’s, it sometimes fails to provide the correct answer. In order to cover the class of pwf’s for which the heuristic technique does not work, in this paper we propose, discuss, and illustrate an extension of the technique into what we call the “slicing method,” which is capable of finding the subadditivity and insensitivity regions of any continuous pwf. |
format | Online Article Text |
id | pubmed-8972790 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-89727902022-04-01 The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions Egozcue, Martín García, Luis Fuentes Zitikis, Ričardas Comput Econ Article A popular rule of thumb, usually called “heuristic technique” in Behavioral Economics, for determining the likelihood insensitivity regions of probability weighting functions (pwf’s) is based on searching for points at which the pwf’s are twice their values at half the points. Although this technique works remarkably well for many commonly used pwf’s, it sometimes fails to provide the correct answer. In order to cover the class of pwf’s for which the heuristic technique does not work, in this paper we propose, discuss, and illustrate an extension of the technique into what we call the “slicing method,” which is capable of finding the subadditivity and insensitivity regions of any continuous pwf. Springer US 2022-04-01 2023 /pmc/articles/PMC8972790/ /pubmed/35382141 http://dx.doi.org/10.1007/s10614-022-10252-8 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Egozcue, Martín García, Luis Fuentes Zitikis, Ričardas The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions |
title | The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions |
title_full | The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions |
title_fullStr | The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions |
title_full_unstemmed | The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions |
title_short | The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions |
title_sort | slicing method: determining insensitivity regions of probability weighting functions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8972790/ https://www.ncbi.nlm.nih.gov/pubmed/35382141 http://dx.doi.org/10.1007/s10614-022-10252-8 |
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