Abstract
We introduce a new mixed distribution of the Erlang distribution that is generated from the convolution of the Extension Exponential distribution denoted by the Mixed Erlang distribution (ME). We derive an exact closed expression of the probability density function which is used to obtain closed expressions of the cumulative function, reliability function, hazard function, moment generating function and kth moment. The method of maximum likelihood and method of moments is used for estimating the model parameters. Two applications to real data sets are given to illustrate the potentiality of this distribution.
| Original language | English |
|---|---|
| Pages (from-to) | 411-420 |
| Number of pages | 10 |
| Journal | Reliability: Theory and Applications |
| Volume | 17 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Mar 2022 |
| Externally published | Yes |
Keywords
- Akaike Information Criterion
- Erlang Distribution
- Extension Exponential Distribution
- Maximum likelihood estimation
- Moments
- Probability Density Function
Fingerprint
Dive into the research topics of 'The New Mixed Erlang Distribution: A Flexible Distribution for Modeling Lifetime Data'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver