Fast algorithms for the quantile regression process
© 2020, Springer-Verlag GmbH Germany, part of Springer Nature. The widespread use of quantile regression methods depends crucially on the existence of fast algorithms. Despite numerous algorithmic improvements, the computation time is still non-negligible because researchers often estimate many quan...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer Science and Business Media LLC
2021
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| Online Access: | https://hdl.handle.net/1721.1/135459 |