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EnglishNearly-Linear Models are a family of neighbourhood models, obtaining lower/upper probabilities from a given probability by a linear affine transformation with barriers. They include a number of known models as special cases, among them the Pari-Mutuel Model, the ε-contamination model, the Total Variation Model and the vacuous lower/upper probabilities. We classified Nearly-Linear models, investigating their consistency properties, in previous work. Here we focus on how to extend those Nearly-Linear Models that are coherent or at least avoid sure loss. We derive formulae for their natural extensions, interpret a specific model as a natural extension itself of a certain class of lower probabilities, and supply a risk measurement interpretation for one of the natural extensions we compute.
| Titolo: | Extending Nearly-Linear Models |
| Autori: | |
| Data di pubblicazione: | 2019 |
| Serie: | |
| Abstract: | Nearly-Linear Models are a family of neighbourhood models, obtaining lower/upper probabilities from a given probability by a linear affine transformation with barriers. They include a number of known models as special cases, among them the Pari-Mutuel Model, the ε-contamination model, the Total Variation Model and the vacuous lower/upper probabilities. We classified Nearly-Linear models, investigating their consistency properties, in previous work. Here we focus on how to extend those Nearly-Linear Models that are coherent or at least avoid sure loss. We derive formulae for their natural extensions, interpret a specific model as a natural extension itself of a certain class of lower probabilities, and supply a risk measurement interpretation for one of the natural extensions we compute. |
| Handle: | http://hdl.handle.net/11368/2945506 |
| Appare nelle tipologie: | 2.1 Contributo in Volume (Capitolo,Saggio) |
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| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| corsato19a.pdf | Articolo pubblicato online | Documento in Versione Editoriale |  | Open Access Visualizza/Apri |
