Zobrazeno 1 - 10
of 331
pro vyhledávání: '"Siem Jan Koopman"'
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
Publikováno v:
Journal of Statistical Software, Vol 41, Iss 01 (2011)
In this paper we review the state space approach to time series analysis and establish the notation that is adopted in this special volume of the Journal of Statistical Software. We first provide some background on the history of state space methods
Externí odkaz:
https://doaj.org/article/4e363cdad8714058a0ee8ffde5571cd1
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
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
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
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
Publikováno v:
Blasques, F, Koopman, S J & Nientker, M 2022, ' A time-varying parameter model for local explosions ', Journal of Econometrics, vol. 227, no. 1, pp. 65-84 . https://doi.org/10.1016/j.jeconom.2021.05.008
Journal of Econometrics, 227(1), 65-84. Elsevier BV
Journal of Econometrics, 227(1), 65-84. Elsevier BV
Financial and economic time series can feature locally explosive behaviour when bubbles are formed. We develop a time-varying parameter model that is capable of describing this behaviour in time series data. Our proposed dynamic model can be used to
Publikováno v:
Winter, J D, Koopman, S J & Hindrayanto, I 2022, ' Joint Decomposition of Business and Financial Cycles : Evidence from Eight Advanced Economies* ', Oxford Bulletin of Economics and Statistics, vol. 84, no. 1, pp. 57-79 . https://doi.org/10.1111/obes.12459
Oxford Bulletin of Economics and Statistics, 84(1), 57-79. Wiley-Blackwell
Oxford Bulletin of Economics and Statistics, 84(1), 57-79. Wiley-Blackwell
We discuss a model-based simultaneous decomposition of multiple time series in short-term and medium-term cyclical dynamics. We associate short-term dynamic features with the business cycle and medium-term dynamic features with the financial cycle. F
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
van de Werve, I, Blasques, F, Koopman, S J & Heres Hoogerkamp, M 2021, ' Dynamic factor models with clustered loadings: Forecasting education flows using unemployment data ', International Journal of Forecasting, vol. 37, no. 4, pp. 1426-1441 . https://doi.org/10.1016/j.ijforecast.2021.01.026
International Journal of Forecasting, 37(4), 1426-1441. Elsevier
International Journal of Forecasting, 37(4), 1426-1441. Elsevier
We propose a dynamic factor model which we use to analyze the relationship between education participation and national unemployment, as well as to forecast the number of students across the many different types of education. By clustering the factor