Exponentially-modified logistic distribution with application to mining and nutrition data
| datacite.alternateIdentifier.citation | Applied Mathematics and Information Sciences, Vol. 12, N° 6, 1109-1116, 2018 | |
| datacite.alternateIdentifier.doi | 10.18576/amis/120605 | es_ES |
| datacite.creator | Reyes, Jimmy | |
| datacite.creator | Venegas, Osvaldo | |
| datacite.creator | Gómez, Héctor | |
| datacite.date | 2018 | |
| datacite.date.issued | 2019-09-27 | |
| datacite.subject | Distribución Gaussiana | es_ES |
| datacite.subject | Distribución Logística | es_ES |
| datacite.subject | Estimaciones de Máxima Verosimilitud | es_ES |
| datacite.subject | Estadísticas | es_ES |
| datacite.title | Exponentially-modified logistic distribution with application to mining and nutrition data | es_ES |
| dc.date.accessioned | 2019-09-27T14:12:03Z | |
| dc.date.available | 2019-09-27T14:12:03Z | |
| dc.description.abstract | In this work we introduce a modification of the exponentially-modified Gaussian distribution. This new distribution is obtained by combining a logistic distribution with an exponential distribution, and is more flexible than other similar distributions. We provide a closed expression for the density function and obtain some important properties useful for making inferences, such as moment estimators and maximum likelihood estimators. By way of illustration, and using real data to show the effectiveness of the new model, we compare it with known related models, showing that the new model achieves a better fit. | es_ES |
| dc.format | es_ES | |
| dc.identifier.uri | http://repositoriodigital.uct.cl/handle/10925/2007 | |
| dc.language.iso | en | es_ES |
| dc.source | Applied Mathematics and Information Sciences | es_ES |
| oaire.resourceType | Artículo de Revista | es_ES |
| uct.catalogador | mlm | es_ES |
| uct.comunidad | Ingeniería | es_ES |
| uct.disciplina | Estadísticas y Probabilidades | es_ES |
| uct.indizacion | SCOPUS | es_ES |