Bootstrap prediction intervals in State Space models
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- Alejandro Rodriguez & Esther Ruiz, 2009. "Bootstrap prediction intervals in state-space models," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(2), pages 167-178, March.
References listed on IDEAS
- Broto, Carmen & Ruiz, Esther, 2006. "Using auxiliary residuals to detect conditional heteroscedasticity in inflation," DES - Working Papers. Statistics and Econometrics. WS ws060402, Universidad Carlos III de Madrid. Departamento de Estadística.
- Lorenzo Pascual & Juan Romo & Esther Ruiz, 2004.
"Bootstrap predictive inference for ARIMA processes,"
Journal of Time Series Analysis,
Wiley Blackwell, vol. 25(4), pages 449-465, July.
- Pascual, L. & Romo, Juan & Ruiz, Esther, 1999. "Bootstrap Predictive Inference for Arima Processes," DES - Working Papers. Statistics and Econometrics. WS 6283, Universidad Carlos III de Madrid. Departamento de Estadística.
- Evans, Martin, 1991. "Discovering the Link between Inflation Rates and Inflation Uncertainty," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 23(2), pages 169-184, May.
- Durbin, James & Koopman, Siem Jan, 2012.
"Time Series Analysis by State Space Methods,"
Oxford University Press,
edition 2, number 9780199641178.
- Tom Doan, "undated". "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- Laurence Ball & Stephen G. Cecchetti, 1990. "Inflation and Uncertainty at Long and Short Horizons," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 21(1), pages 215-254.
- Andrew Harvey & Esther Ruiz & Neil Shephard, 1994. "Multivariate Stochastic Variance Models," Review of Economic Studies, Oxford University Press, vol. 61(2), pages 247-264.
- Cavaglia, Stefano, 1992. "The persistence of real interest differentials: A Kalman filtering approach," Journal of Monetary Economics, Elsevier, vol. 29(3), pages 429-443, June.
- Danny Pfeffermann & Richard Tiller, 2005. "Bootstrap Approximation to Prediction MSE for State-Space Models with Estimated Parameters," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(6), pages 893-916, November.
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- Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013.
"Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models,"
International Journal of Forecasting,
Elsevier, vol. 29(3), pages 411-430.
- 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.
- García-Martos, Carolina & Rodríguez, Julio & Sánchez, María Jesús, 2013. "Modelling and forecasting fossil fuels, CO2 and electricity prices and their volatilities," Applied Energy, Elsevier, vol. 101(C), pages 363-375.
- Thiago R. Santos & Glaura C. Franco & Dani Gamerman, 2010. "Comparison of Classical and Bayesian Approaches for Intervention Analysis," International Statistical Review, International Statistical Institute, vol. 78(2), pages 218-239, August.
- repec:eme:aecozz:s0731-905320150000035010 is not listed on IDEAS
- Rodríguez, Alejandro & Ruiz, Esther, 2012.
"Bootstrap prediction mean squared errors of unobserved states based on the Kalman filter with estimated parameters,"
Computational Statistics & Data Analysis,
Elsevier, vol. 56(1), pages 62-74, January.
- Rodríguez, Alejandro & Ruiz, Esther, 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 Estadística.
- David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017. "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers 9/17, Monash University, Department of Econometrics and Business Statistics.
- Lorenzo Boldrini, 2015. "Forecasting the Global Mean Sea Level, a Continuous-Time State-Space Approach," CREATES Research Papers 2015-40, Department of Economics and Business Economics, Aarhus University.
- García-Martos, Carolina & Rodríguez, Julio & Sánchez, María Jesús, 2011. "Forecasting electricity prices and their volatilities using Unobserved Components," Energy Economics, Elsevier, vol. 33(6), pages 1227-1239.
- Pilar Poncela & Esther Ruiz, 2016.
"Small- Versus Big-Data Factor Extraction in Dynamic Factor Models: An Empirical Assessment,"
Advances in Econometrics,in: Dynamic Factor Models, volume 35, pages 401-434
Emerald Publishing Ltd.
- Ruiz, Esther & 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 Estadística.
More about this item
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2008-04-04 (All new papers)
- NEP-ECM-2008-04-04 (Econometrics)
- NEP-ETS-2008-04-04 (Econometric Time Series)
- NEP-FOR-2008-04-04 (Forecasting)
- NEP-ORE-2008-04-04 (Operations Research)
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