Generalized extreme value distribution with time-dependence using the AR and MA models in state space form
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- Nakajima, Jouchi & Kunihama, Tsuyoshi & Omori, Yasuhiro & Frühwirth-Schnatter, Sylvia, 2012. "Generalized extreme value distribution with time-dependence using the AR and MA models in state space form," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3241-3259.
- Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori & Sylvia Fruwirth-Scnatter, 2009. "Generalized Extreme Value Distribution with Time-Dependence Using the AR and MA Models in State Space Form," IMES Discussion Paper Series 09-E-32, Institute for Monetary and Economic Studies, Bank of Japan.
- Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori & Sylvia Fruhwirth-Schnatter, 2011. "Generalized Extreme Value Distribution with Time-Dependence Using the AR and MA Models in State Space Form," CIRJE F-Series CIRJE-F-782, CIRJE, Faculty of Economics, University of Tokyo.
References listed on IDEAS
- Chib, Siddhartha, 2001. "Markov chain Monte Carlo methods: computation and inference," Handbook of Econometrics,in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 57, pages 3569-3649 Elsevier.
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- Omori, Yasuhiro & Watanabe, Toshiaki, 2008.
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CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Auray, Stéphane & Eyquem, Aurélien & Jouneau-Sion, Frédéric, 2014.
"Modeling tails of aggregate economic processes in a stochastic growth model,"
Computational Statistics & Data Analysis,
Elsevier, vol. 76(C), pages 76-94.
- Stéphane Auray & Aurélien Eyquem & Fréderic Jouneau-Sion, 2012. "Modelling Tails of Aggregated Economic Processes in a Stochastic Growth Model," Working Papers 2012-29, Center for Research in Economics and Statistics.
- Stéphane Auray & Aurélien Eyquem & Frédéric Jouneau-Sion, 2014. "Modelling Tails of Aggregated Economic Processes in a Stochastic Growth Model," Post-Print halshs-00995703, HAL.
- Wang, Yixin & So, Mike K.P., 2016. "A Bayesian hierarchical model for spatial extremes with multiple durations," Computational Statistics & Data Analysis, Elsevier, vol. 95(C), pages 39-56.
- repec:eee:phsmap:v:490:y:2018:i:c:p:754-773 is not listed on IDEAS
More about this item
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2009-11-27 (All new papers)
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