The proportional likelihood ratio order and applications
In this paper, we introduce a new stochastic order between continuous non-negative random variables called the PLR (proportional likelihood ratio) order, which is closely related to the usual likelihood ratio order. The PLR order can be used to characterize random variables whose logarithms have log...
| Autores: | , |
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| Formato: | artículo |
| Fecha de publicación: | 2001 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2099/4156 |
| Acesso em linha: | https://hdl.handle.net/2099/4156 |
| Access Level: | acceso abierto |
| Palavra-chave: | Distribution (Probability theory) Probability Distribució (Teoria de la probabilitat) Probabilitats Classificació AMS::60 Probability theory and stochastic processes::60E Distribution theory Classificació AMS::60 Probability theory and stochastic processes::60K Special processes |
| Resumo: | In this paper, we introduce a new stochastic order between continuous non-negative random variables called the PLR (proportional likelihood ratio) order, which is closely related to the usual likelihood ratio order. The PLR order can be used to characterize random variables whose logarithms have log-concave (log-convex) densities. Many income random variables satisfy this property and they are said to have the IPLR (increasing proportional likelihood ratio) property (DPLR property). As an application, we show that the IPLR and DPLR properties are sufficient conditions for the Lorenz ordering of truncated distributions. |
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