IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v29y1999i4p387-410.html
   My bibliography  Save this article

Hyperparameter estimation in forecast models

Author

Listed:
  • Lopes, Hedibert Freitas
  • Moreira, Ajax R. Bello
  • Schmidt, Alexandra Mello

Abstract

No abstract is available for this item.

Suggested Citation

  • Lopes, Hedibert Freitas & Moreira, Ajax R. Bello & Schmidt, Alexandra Mello, 1999. "Hyperparameter estimation in forecast models," Computational Statistics & Data Analysis, Elsevier, vol. 29(4), pages 387-410, February.
    • Handle: RePEc:eee:csdana:v:29:y:1999:i:4:p:387-410
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(98)00078-4
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. John Geweke, 1994. "Bayesian comparison of econometric models," Working Papers 532, Federal Reserve Bank of Minneapolis.
    2. Koop, G, 1992. "Aggregate Shocks and Macroeconomic Fluctuations: A Bayesian Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(4), pages 395-411, Oct.-Dec..
    3. van Dijk, H. K. & Kloek, T., 1980. "Further experience in Bayesian analysis using Monte Carlo integration," Journal of Econometrics, Elsevier, vol. 14(3), pages 307-328, December.
    4. Lima, Elcyon Caiado Rocha & Migon, Hélio S. & Lopes, Hedibert Freitas, 1993. "Efeitos dinâmicos dos choques de oferta e demanda agregadas sobre o nível de atividade econômica do Brasil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 47(2), April.
    5. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    6. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    7. Michael K Pitt & Neil Shephard, "undated". "Filtering via simulation: auxiliary particle filters," Economics Papers 1997-W13, Economics Group, Nuffield College, University of Oxford.
    8. Alexandra Mello Schmidt & Dani Gamerman & Ajax Moreira, 1999. "An adaptive resampling scheme for cycle estimation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(5), pages 619-641.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2020. "Choosing Prior Hyperparameters: With Applications to Time-Varying Parameter Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 124-136, January.
    2. 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.
    3. Ajax R. B. Moreira & Dani Gamerman, 2015. "Bayesian Analysis of Econometric Time Series Models Using Hybrid Integration Rules," Discussion Papers 0105, Instituto de Pesquisa Econômica Aplicada - IPEA.
    4. Lusompa, Amaze, 2019. "Local Projections, Autocorrelation, and Efficiency," MPRA Paper 99856, University Library of Munich, Germany, revised 11 Apr 2020.
    5. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015. "Prior Selection for Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
    6. Huerta, Gabriel & Lopes, Hedibert Freitas, 2000. "Bayesian forecasting and inference in latent structure for the Brazilian Industrial Production Index," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 20(1), May.
    7. Ho, Paul, 2023. "Global robust Bayesian analysis in large models," Journal of Econometrics, Elsevier, vol. 235(2), pages 608-642.
    8. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2016. "Choosing Prior Hyperparameters," Working Paper 16-9, Federal Reserve Bank of Richmond.
    9. Lee, Namgil & Choi, Hyemi & Kim, Sung-Ho, 2016. "Bayes shrinkage estimation for high-dimensional VAR models with scale mixture of normal distributions for noise," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 250-276.
    10. Alexandra Mello Schmidt & Dani Gamerman & Ajax Moreira, 1999. "An adaptive resampling scheme for cycle estimation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(5), pages 619-641.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mr. Matteo Ciccarelli & Mr. Alessandro Rebucci, 2003. "Bayesian Vars: A Survey of the Recent Literature with An Application to the European Monetary System," IMF Working Papers 2003/102, International Monetary Fund.
    2. Canova, Fabio & Ciccarelli, Matteo, 2004. "Forecasting and turning point predictions in a Bayesian panel VAR model," Journal of Econometrics, Elsevier, vol. 120(2), pages 327-359, June.
    3. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    4. Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 349-366, November.
    5. Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez, 2001. "Comparing dynamic equilibrium economies to data," FRB Atlanta Working Paper 2001-23, Federal Reserve Bank of Atlanta.
    6. Florian Huber & Tamás Krisztin & Philipp Piribauer, 2017. "Forecasting Global Equity Indices Using Large Bayesian Vars," Bulletin of Economic Research, Wiley Blackwell, vol. 69(3), pages 288-308, July.
    7. Giannone, Domenico & Lenza, Michele & Momferatou, Daphne & Onorante, Luca, 2014. "Short-term inflation projections: A Bayesian vector autoregressive approach," International Journal of Forecasting, Elsevier, vol. 30(3), pages 635-644.
    8. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    9. Tomasz Woźniak, 2016. "Bayesian Vector Autoregressions," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 49(3), pages 365-380, September.
    10. Raviv, Eran & Bouwman, Kees E. & van Dijk, Dick, 2015. "Forecasting day-ahead electricity prices: Utilizing hourly prices," Energy Economics, Elsevier, vol. 50(C), pages 227-239.
    11. Mr. Serhat Solmaz & Marzie Taheri Sanjani, 2015. "How External Factors Affect Domestic Economy: Nowcasting an Emerging Market," IMF Working Papers 2015/269, International Monetary Fund.
    12. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019. "How Sensitive Are VAR Forecasts to Prior Hyperparameters? An Automated Sensitivity Analysis," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A, volume 40, pages 229-248, Emerald Group Publishing Limited.
    13. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2022. "The global component of inflation volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 700-721, June.
    14. Demeshev, Boris & Malakhovskaya, Oxana, 2016. "BVAR mapping," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 43, pages 118-141.
    15. Helmut Lütkepohl, 2013. "Vector autoregressive models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 6, pages 139-164, Edward Elgar Publishing.
    16. Moreira, Ricardo Ramalhete, 2016. "Measuring the Monetary Policy’s Structural Credibility by the Expected Inflation Determinants: a Kalman Filter Approach for Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 36(2), November.
    17. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    18. Silvia Miranda-Agrippino & Giovanni Ricco, 2021. "The Transmission of Monetary Policy Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(3), pages 74-107, July.
    19. Dahem, Ahlem, 2015. "Short term Bayesian inflation forecasting for Tunisia," MPRA Paper 66702, University Library of Munich, Germany.
    20. Kaabia, Olfa & Abid, Ilyes & Guesmi, Khaled, 2013. "Does Bayesian shrinkage help to better reflect what happened during the subprime crisis?," Economic Modelling, Elsevier, vol. 31(C), pages 423-432.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:29:y:1999:i:4:p:387-410. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.