| Title |
Reliability analysis using an exponential power model with bathtub-shaped failure rate function: a Bayes study
|
|---|---|
| Published in |
SpringerPlus, July 2016
|
| DOI | 10.1186/s40064-016-2722-3 |
| Pubmed ID | |
| Authors |
Romana Shehla, Athar Ali Khan |
| Abstract |
Models with bathtub-shaped hazard function have been widely accepted in the field of reliability and medicine and are particularly useful in reliability related decision making and cost analysis. In this paper, the exponential power model capable of assuming increasing as well as bathtub-shape, is studied. This article makes a Bayesian study of the same model and simultaneously shows how posterior simulations based on Markov chain Monte Carlo algorithms can be straightforward and routine in R. The study is carried out for complete as well as censored data, under the assumption of weakly-informative priors for the parameters. In addition to this, inference interest focuses on the posterior distribution of non-linear functions of the parameters. Also, the model has been extended to include continuous explanatory variables and R-codes are well illustrated. Two real data sets are considered for illustrative purposes. |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 8% |
| Unknown | 11 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 33% |
| Student > Ph. D. Student | 4 | 33% |
| Professor | 1 | 8% |
| Unknown | 3 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 2 | 17% |
| Engineering | 2 | 17% |
| Mathematics | 1 | 8% |
| Psychology | 1 | 8% |
| Agricultural and Biological Sciences | 1 | 8% |
| Other | 2 | 17% |
| Unknown | 3 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 15 March 2018.
All research outputs
#8,051,914
of 24,201,556 outputs
Outputs from SpringerPlus
#513
of 1,857 outputs
Outputs of similar age
#129,679
of 361,378 outputs
Outputs of similar age from SpringerPlus
#71
of 235 outputs
Altmetric has tracked 24,201,556 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,857 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has gotten more attention than average, scoring higher than 66% of its peers.
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We're also able to compare this research output to 235 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.