A New Extension of the Exponentiated Weibull Model Mathematical Properties and Modelling
Recently, several writers have extended the exponentiated Weibull distribution. The five-parameter exponentiated Weibull-exponentiated Weibull (EW-EW) distribution is introduced. In terms of fit, the EW-EW distribution outperforms the EW distribution. Some EW-EW distribution features, such as precis...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | Journal of Function Spaces |
| Online Access: | http://dx.doi.org/10.1155/2022/4669412 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Recently, several writers have extended the exponentiated Weibull distribution. The five-parameter exponentiated Weibull-exponentiated Weibull (EW-EW) distribution is introduced. In terms of fit, the EW-EW distribution outperforms the EW distribution. Some EW-EW distribution features, such as precise formulas for ordinary moments, quantile, median, and order statistics, are found. Model parameters were estimated using the maximum likelihood technique (ML). The behavior of the various estimators was investigated using a simulated exercise. A medical dataset was utilized to evaluate the practical importance of the EW-EW distribution using additional criteria such as the Akaike information criterion (AKINC), the correct AKINC (COAKINC), the Bayesian INC (BINC), and the Hannan-Quinn INC (HQINC). In terms of performance, we show that the EW-EW distribution beats other models. |
|---|---|
| ISSN: | 2314-8888 |