The zero-truncated discrete transmuted generalized inverse Weibull distribution and its applications
In this article, a new distribution for count data analysis is introduced. Firstly, the Discrete Transmuted Generalized Inverse Weibull distribution (DTGIW) is constructed. Consequently, some useful sub-models are discussed. Secondly, the ZeroTruncated Discrete Transmuted Generalized Inverse Weibul...
Guardado en:
| Autores principales: | , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Prince of Songkla University
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/1bde874efa6c47d9b13c54e0c3d4bf74 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | In this article, a new distribution for count data analysis is introduced. Firstly, the Discrete Transmuted Generalized
Inverse Weibull distribution (DTGIW) is constructed. Consequently, some useful sub-models are discussed. Secondly, the ZeroTruncated Discrete Transmuted Generalized Inverse Weibull distribution (ZT-DTGIW) is introduced. We present probability
mass function of the proposed distribution and some plots of those functions for illustration the behaviors of the distribution. We
employed the maximum likelihood estimation (MLE) technique for model parameter estimation. For the purpose of verification
of the MLE performance, the simulation study of parameter estimation using MLE is illustrated. Finally, some real data sets are
applied to illustrate the goodness of fit of the proposed distribution, which is compared with the zero-truncated discrete inverse
Weibull and zero-truncated Poisson distributions. |
|---|