Likelihood functions for state space models with diffuse initial conditions
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- Marc K. Francke & Siem Jan Koopman & Aart de Vos, 2008. "Likelihood Functions for State Space Models with Diffuse Initial Conditions," Tinbergen Institute Discussion Papers 08-040/4, Tinbergen Institute.
References listed on IDEAS
- Barr Rosenberg, 1973. "Random Coefficients Models: The Analysis of a Cross Section of Time Series by Stochastically Convergent Parameter Regression," NBER Chapters,in: Annals of Economic and Social Measurement, Volume 2, number 4, pages 399-428 National Bureau of Economic Research, Inc.
- Durbin, James & Koopman, Siem Jan, 2012.
"Time Series Analysis by State Space Methods,"
Oxford University Press,
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- 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.
- Francke, Marc K. & de Vos, Aart F., 2007. "Marginal likelihood and unit roots," Journal of Econometrics, Elsevier, vol. 137(2), pages 708-728, April.
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- Marczak, Martyna & Proietti, Tommaso & Grassi, Stefano, 2018.
"A data-cleaning augmented Kalman filter for robust estimation of state space models,"
Econometrics and Statistics,
Elsevier, vol. 5(C), pages 107-123.
- Marczak, Martyna & Proietti, Tommaso & Grassi, Stefano, 2015. "A data-cleaning augmented Kalman filter for robust estimation of state space models," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2015, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
- Martyna Marczak & Tommaso Proietti & Stefano Grassi, 2016. "A Data–Cleaning Augmented Kalman Filter for Robust Estimation of State Space Models," CEIS Research Paper 374, Tor Vergata University, CEIS, revised 31 Mar 2016.
- Søren Johansen & Marco Riani & Anthony C. Atkinson, 2012.
"The Selection of ARIMA Models with or without Regressors,"
12-17, University of Copenhagen. Department of Economics.
- Søren Johansen & Marco Riani & Anthony C. Atkinson, 2012. "The Selection of ARIMA Models with or without Regressors," CREATES Research Papers 2012-46, Department of Economics and Business Economics, Aarhus University.
- repec:spr:empeco:v:53:y:2017:i:4:d:10.1007_s00181-016-1179-0 is not listed on IDEAS
- Tommaso Proietti & Alessandra Luati, 2013.
"Maximum likelihood estimation of time series models: the Kalman filter and beyond,"
Chapters,in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362
Edward Elgar Publishing.
- Luati, Alessandra & Proietti, Tommaso, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Working Papers 2012_02, University of Sydney Business School, Discipline of Business Analytics.
- Tommaso, Proietti & Alessandra, Luati, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," MPRA Paper 39600, University Library of Munich, Germany.
- José Casals & Sonia Sotoca & Miguel Jerez, 2012. "Minimally Conditioned Likelihood for a Nonstationary State Space Model," Documentos de Trabajo del ICAE 2012-04, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
More about this item
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
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