Machine learning for regularized survey forecast combination : partially-egalitarian LASSO and its derivatives
Francis X. Diebold, Minchul Shin
| Year of publication: |
2019
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|---|---|
| Authors: | Diebold, Francis X. ; Shin, Minchul |
| Published in: |
International journal of forecasting. - Amsterdam [u.a.] : Elsevier, ISSN 0169-2070, ZDB-ID 283943-X. - Vol. 35.2019, 4, p. 1679-1691
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| Subject: | Forecast combination | Forecast surveys | LASSO | Model selection | Regularization | Shrinkage | Theorie | Theory | Prognoseverfahren | Forecasting model | Regressionsanalyse | Regression analysis | Künstliche Intelligenz | Artificial intelligence | Wirtschaftsprognose | Economic forecast | Aggregation | Eurozone | Euro area | Modellierung | Scientific modelling |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Notes: | Erratum enthalten in: International journal of forecasting, Volume 37, issue 3 (July/September 2021), Seite 1308-1309 |
| Other identifiers: | 10.1016/j.ijforecast.2018.09.006 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012305515