Entropy Estimation From Ranked Set Samples With Application to Test of Fit
This article deals with entropy estimation using ranked set sampling (RSS). Some estimators are developed based on the empirical distribution function and its nonparametric maximum likelihood competitor. The suggested entropy estimators have smaller root mean squared errors than the other entropy es...
- Autores:
-
Zamanzade, Ehsan
Mahdizadeh, Mahdi
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2017
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/66496
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/66496
http://bdigital.unal.edu.co/67524/
- Palabra clave:
- 51 Matemáticas / Mathematics
31 Colecciones de estadística general / Statistics
Judgment ranking
Goodness of fit test
Entropy estimation
Bondad de ajuste
Estimación de entropía
Ranking de juicios
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | This article deals with entropy estimation using ranked set sampling (RSS). Some estimators are developed based on the empirical distribution function and its nonparametric maximum likelihood competitor. The suggested entropy estimators have smaller root mean squared errors than the other entropy estimators in the literature. The proposed estimators are then used to construct goodness of fit tests for inverse Gaussian distribution. |
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