| Title |
Further results involving Marshall–Olkin log-logistic distribution: reliability analysis, estimation of the parameter, and applications
|
|---|---|
| Published in |
SpringerPlus, March 2016
|
| DOI | 10.1186/s40064-016-2007-x |
| Pubmed ID | |
| Authors |
Arwa M. Alshangiti, M. Kayid, B. Alarfaj |
| Abstract |
The purpose of this paper is to provide further study of the Marshall-Olkin log-logistic model that was first described by Gui (Appl Math Sci 7:3947-3961, 2013). This model is both useful and practical in areas such as reliability and life testing. Some statistical and reliability properties of this model are presented including moments, reversed hazard rate and mean residual life functions, among others. Maximum likelihood estimation of the parameters of the model is discussed. Finally, a real data set is analyzed and it is observed that the presented model provides a better fit than the log-logistic model. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 6 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 2 | 33% |
| Lecturer | 1 | 17% |
| Other | 1 | 17% |
| Professor | 1 | 17% |
| Student > Ph. D. Student | 1 | 17% |
| Other | 0 | 0% |
| Readers by discipline | Count | As % |
|---|---|---|
| Mathematics | 4 | 67% |
| Medicine and Dentistry | 1 | 17% |
| Engineering | 1 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 April 2016.
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#15,366,818
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Outputs from SpringerPlus
#932
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Outputs of similar age
#180,521
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Outputs of similar age from SpringerPlus
#95
of 181 outputs
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