Bootstrap prediction intervals in state–space models
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DOI: 10.1111/j.1467-9892.2008.00604.x
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- Rodríguez, Alejandro, 2008. "Bootstrap prediction intervals in State Space models," DES - Working Papers. Statistics and Econometrics. WS ws081104, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
References listed on IDEAS
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Citations
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Cited by:
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- Jason Ng & Catherine S. Forbes & Gael M. Martin & Brendan P.M. McCabe, 2011. "Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models," Monash Econometrics and Business Statistics Working Papers 11/11, Monash University, Department of Econometrics and Business Statistics.
- Kim, Jae H. & Wong, Kevin & Athanasopoulos, George & Liu, Shen, 2011.
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- Kim, Jae H. & Wong, Kevin & Athanasopoulos, George & Liu, Shen, 2011. "Beyond point forecasting: Evaluation of alternative prediction intervals for tourist arrivals," International Journal of Forecasting, Elsevier, vol. 27(3), pages 887-901, July.
- Jae H. Kim & Haiyang Song & Kevin Wong & George Athanasopoulos & Shen Liu, 2008. "Beyond point forecasting: evaluation of alternative prediction intervals for tourist arrivals," Monash Econometrics and Business Statistics Working Papers 11/08, Monash University, Department of Econometrics and Business Statistics, revised Oct 2009.
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- Poncela, Pilar, 2015. "Small versus big-data factor extraction in Dynamic Factor Models: An empirical assessment," DES - Working Papers. Statistics and Econometrics. WS ws1502, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
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Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 62-74, January.
- Rodríguez, Alejandro, 2010. "Bootstrap prediction mean squared errors of unobserved states based on the Kalman filter with estimated parameters," DES - Working Papers. Statistics and Econometrics. WS ws100301, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
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- Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.
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