The family of log-skew-normal alpha-power distributions using precipitation data
We present a new set of distributions for positive data based on a skewnormalalpha-power (PSN) model including a new parameter which in turnmakes the log-skew-normal alpha-power (LPSN) model more flexible thanboth the log-normal (LN) model and log-skew-normal (LSN) model. TheLPSN model contains the...
- Autores:
-
Martínez-Flórez, Guillermo
Vergara-Cardozo, Sandra
González, Luz Mery
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2013
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/73205
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/73205
http://bdigital.unal.edu.co/37680/
- Palabra clave:
- symmetry
Fisher information matrix
Kurtosis
Likelihood ratio test
Maximum likelihood estimator.
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | We present a new set of distributions for positive data based on a skewnormalalpha-power (PSN) model including a new parameter which in turnmakes the log-skew-normal alpha-power (LPSN) model more flexible thanboth the log-normal (LN) model and log-skew-normal (LSN) model. TheLPSN model contains the LN model and LSN model as special cases. Furthermore,it models positive data with asymmetry and kurtosis larger thanthe one permitted by the LN distribution. Precipitation data illustrates theusefulness of the LPSN model being less influenced by outliers. |
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