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Mendeley readers
| Chapter title |
Subspace Methods
|
|---|---|
| Chapter number | 9 |
| Book title |
Macroeconomic Forecasting in the Era of Big Data
|
| Published by |
Springer, Cham, November 2019
|
| DOI | 10.1007/978-3-030-31150-6_9 |
| Book ISBNs |
978-3-03-031149-0, 978-3-03-031150-6
|
| Authors |
Tom Boot, Didier Nibbering |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 2% |
| Israel | 1 | 2% |
| Colombia | 1 | 2% |
| Austria | 1 | 2% |
| Unknown | 39 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 28% |
| Researcher | 8 | 19% |
| Student > Master | 7 | 16% |
| Professor | 4 | 9% |
| Professor > Associate Professor | 3 | 7% |
| Other | 4 | 9% |
| Unknown | 5 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 13 | 30% |
| Computer Science | 7 | 16% |
| Mathematics | 5 | 12% |
| Earth and Planetary Sciences | 5 | 12% |
| Economics, Econometrics and Finance | 3 | 7% |
| Other | 5 | 12% |
| Unknown | 5 | 12% |