| Title |
A practitioner’s guide to Bayesian estimation of discrete choice dynamic programming models
|
|---|---|
| Published in |
Quantitative Marketing and Economics, February 2012
|
| DOI | 10.1007/s11129-012-9119-6 |
| Authors |
Andrew T. Ching, Susumu Imai, Masakazu Ishihara, Neelam Jain |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 1% |
| United States | 2 | 1% |
| Japan | 2 | 1% |
| Belgium | 1 | <1% |
| Germany | 1 | <1% |
| Hong Kong | 1 | <1% |
| Korea, Republic of | 1 | <1% |
| Unknown | 126 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 52 | 38% |
| Researcher | 20 | 15% |
| Professor > Associate Professor | 16 | 12% |
| Student > Master | 12 | 9% |
| Professor | 7 | 5% |
| Other | 19 | 14% |
| Unknown | 10 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Economics, Econometrics and Finance | 53 | 39% |
| Business, Management and Accounting | 40 | 29% |
| Social Sciences | 8 | 6% |
| Engineering | 5 | 4% |
| Mathematics | 4 | 3% |
| Other | 9 | 7% |
| Unknown | 17 | 13% |
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 28 September 2016.
All research outputs
#13,973,867
of 23,911,072 outputs
Outputs from Quantitative Marketing and Economics
#91
of 111 outputs
Outputs of similar age
#89,970
of 158,974 outputs
Outputs of similar age from Quantitative Marketing and Economics
#1
of 2 outputs
Altmetric has tracked 23,911,072 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 111 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.7. This one is in the 18th percentile – i.e., 18% 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 158,974 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them