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Application of air ...
Application of air quality combination forecasting to Bogota
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Westerlund, J. (författare)
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Urbain, J. P. (författare)
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- Bonilla, Jorge, 1975 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för nationalekonomi med statistik, Enheten för miljöekonomi,Department of Economics, Environmental Economics Unit
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(creator_code:org_t)
- Elsevier BV, 2014
- 2014
- Engelska.
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Ingår i: Atmospheric Environment. - : Elsevier BV. - 1352-2310. ; 89, s. 22-28
- Relaterad länk:
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https://gup.ub.gu.se...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- The bulk of existing work on the statistical forecasting of air quality is based on either neural networks or linear regressions, which are both subject to important drawbacks. In particular, while neural networks are complicated and prone to in-sample overfitting, linear regressions are highly dependent on the specification of the regression function. The present paper shows how combining linear regression forecasts can be used to circumvent all of these problems. The usefulness of the proposed combination approach is verified using both Monte Carlo simulation and an extensive application to air quality in Bogota, one of the largest and most polluted cities in Latin America. (C) 2014 Elsevier Ltd. All rights reserved.
Ämnesord
- SAMHÄLLSVETENSKAP -- Ekonomi och näringsliv (hsv//swe)
- SOCIAL SCIENCES -- Economics and Business (hsv//eng)
Nyckelord
- Air quality forecasting
- Bogota
- Forecast combination
- Neural networks
- MISSING VALUES
- POLLUTION
- IMPUTATION
- GREECE
- MODEL
- SO2
- Environmental Sciences
- Meteorology & Atmospheric Sciences
- ENVIRONMENTAL SCIENCES
- METEOROLOGY & ATMOSPHERIC SCIENCES
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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