Zobrazeno 1 - 10
of 851
pro vyhledávání: '"Siem Jan Koopman"'
Autor:
Judge, Guy, Ninomiya, Yasushi
Publikováno v:
The Economic Journal, 2000 Nov 01. 110(467), F721-F738.
Externí odkaz:
https://www.jstor.org/stable/2667774
Autor:
Judge, Guy
Publikováno v:
The Economic Journal, 1996 Jul 01. 106(437), 1106-1115.
Externí odkaz:
https://www.jstor.org/stable/2235399
Publikováno v:
Technometrics, 2006 Feb 01. 48(1), 156-156.
Externí odkaz:
https://www.jstor.org/stable/25471141
Akademický článek
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Autor:
James Mitchell
Publikováno v:
International Journal of Forecasting. 30:585-588
Factor models have become an important tool in the modern forecaster’s toolkit. They provide a means of producing forecasts when the number of indicator series, N , exceeds the number of time series observations, T . A further perceived benefit is
Autor:
Siem Jan Koopman, Eric Hillebrand
Dynamic factor models (DFM) constitute an active and growing area of research, both in econometrics, in macroeconomics, and in finance. Many applications lie at the center of policy questions raised by the recent financial crises, such as the connect
Providing a practical introduction to state space methods as applied to unobserved components time series models, also known as structural time series models, this book introduces time series analysis using state space methodology to readers who are
Publikováno v:
Nature, 616(7956), E1-E3. Nature Publishing Group
Bennedsen, M, Hillebrand, E & Koopman, S J 2023, ' On the evidence of a trend in the CO2 airborne fraction ', Nature, vol. 616, no. 7956, pp. E1-E3 . https://doi.org/10.1038/s41586-023-05871-6
Bennedsen, M, Hillebrand, E & Koopman, S J 2023, ' On the evidence for a trend in the CO2 airborne fraction? ', Nature (Matters Arising) . https://doi.org/10.1038/s41586-023-05871-6
Bennedsen, M, Hillebrand, E & Koopman, S J 2023, ' On the evidence of a trend in the CO2 airborne fraction ', Nature, vol. 616, no. 7956, pp. E1-E3 . https://doi.org/10.1038/s41586-023-05871-6
Bennedsen, M, Hillebrand, E & Koopman, S J 2023, ' On the evidence for a trend in the CO2 airborne fraction? ', Nature (Matters Arising) . https://doi.org/10.1038/s41586-023-05871-6
In a paper recently published in this journal, van Marle et al. (van Marle et al., 2022) introduce an interesting new data set for land use and land cover change CO2 emissions (LULCC) that they use to study whether a trend is present in the airborne
Autor:
Desislava Petrova, Rachel Lowe, Anna Stewart-Ibarra, Joan Ballester, Siem Jan Koopman, Xavier Rodó
Publikováno v:
Climate Services, Vol 15, Iss , Pp - (2019)
Long-lead forecasts of El Niño events are lacking despite their enormous societal and economic impacts. These climatic events lead to floods and droughts in many tropical regions, and damage agriculture and the economy in poor countries. Due to thei
Externí odkaz:
https://doaj.org/article/c0a76aef15504944aed0b5b673476c08
Autor:
Jens A. de Bruijn, James E. Daniell, Antonios Pomonis, Rashmin Gunasekera, Joshua Macabuag, Marleen C. de Ruiter, Siem Jan Koopman, Nadia Bloemendaal, Hans de Moel, Jeroen C.J.H. Aerts
Publikováno v:
de Bruijn, J A, Daniell, J E, Pomonis, A, Gunasekera, R, Macabuag, J, de Ruiter, M C, Koopman, S J, Bloemendaal, N, de Moel, H & Aerts, J C J H 2022, ' Using rapid damage observations for Bayesian updating of hurricane vulnerability functions: A case study of Hurricane Dorian using social media ', International Journal of Disaster Risk Reduction, vol. 72, 102839, pp. 1-16 . https://doi.org/10.1016/j.ijdrr.2022.102839
International Journal of Disaster Risk Reduction, 72, Art.-Nr.: 102839
International Journal of Disaster Risk Reduction, 72:102839, 1-16. Elsevier
de Bruijn, J A, Daniell, J E, Pomonis, A, Gunasekera, R, Macabuag, J, de Ruiter, M C, Koopman, S J, Bloemendaal, N, de Moel, H & Aerts, J C J H 2022, ' Using rapid damage observations for Bayesian updating of hurricane vulnerability functions : A case study of Hurricane Dorian using social media ', International Journal of Disaster Risk Reduction, vol. 72, 102839 . https://doi.org/10.1016/j.ijdrr.2022.102839
International Journal of Disaster Risk Reduction, 72, Art.-Nr.: 102839
International Journal of Disaster Risk Reduction, 72:102839, 1-16. Elsevier
de Bruijn, J A, Daniell, J E, Pomonis, A, Gunasekera, R, Macabuag, J, de Ruiter, M C, Koopman, S J, Bloemendaal, N, de Moel, H & Aerts, J C J H 2022, ' Using rapid damage observations for Bayesian updating of hurricane vulnerability functions : A case study of Hurricane Dorian using social media ', International Journal of Disaster Risk Reduction, vol. 72, 102839 . https://doi.org/10.1016/j.ijdrr.2022.102839
Rapid impact assessments immediately after disasters are crucial to enable rapid and effective mobilization of resources for response and recovery efforts. These assessments are often performed by analysing the three components of risk: hazard, expos