| Title |
Thermodynamic integration via differential evolution: A method for estimating marginal likelihoods
|
|---|---|
| Published in |
Behavior Research Methods, January 2019
|
| DOI | 10.3758/s13428-018-1172-y |
| Pubmed ID | |
| Authors |
Nathan J. Evans, Jeffrey Annis |
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 % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 28% |
| Student > Doctoral Student | 2 | 11% |
| Researcher | 2 | 11% |
| Lecturer | 1 | 6% |
| Student > Bachelor | 1 | 6% |
| Other | 3 | 17% |
| Unknown | 4 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 6 | 33% |
| Computer Science | 3 | 17% |
| Agricultural and Biological Sciences | 1 | 6% |
| Mathematics | 1 | 6% |
| Neuroscience | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 6 | 33% |
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 15 January 2019.
All research outputs
#22,767,715
of 25,385,509 outputs
Outputs from Behavior Research Methods
#2,100
of 2,526 outputs
Outputs of similar age
#386,150
of 446,116 outputs
Outputs of similar age from Behavior Research Methods
#34
of 39 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,526 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 446,116 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.