IDEAS home Printed from https://ideas.repec.org/p/tiu/tiutis/3fff240d-a587-4537-ba5f-22dcadd3f3b1.html
   My bibliography  Save this paper

Multivariate Student -t Regression Models : Pitfalls and Inference

Author

Listed:
  • Fernández, C.
  • Steel, M.F.J.

    (Tilburg University, School of Economics and Management)

Abstract

No abstract is available for this item.

Suggested Citation

  • Fernández, C. & Steel, M.F.J., 1997. "Multivariate Student -t Regression Models : Pitfalls and Inference," Other publications TiSEM 3fff240d-a587-4537-ba5f-2, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:3fff240d-a587-4537-ba5f-22dcadd3f3b1
    as

    Download full text from publisher

    File URL: https://pure.uvt.nl/ws/portalfiles/portal/526576/8.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Liu, C., 1995. "Missing Data Imputation Using the Multivariate t Distribution," Journal of Multivariate Analysis, Elsevier, vol. 53(1), pages 139-158, April.
    2. Geweke, J, 1993. "Bayesian Treatment of the Independent Student- t Linear Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 19-40, Suppl. De.
    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. Manuel Galea & Heleno Bolfarine & Filidor Vilcalabra, 2002. "Influence diagnostics for the structural errors-in-variables model under the Student-t distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(8), pages 1191-1204.
    2. David Cademartori & Cecilia Romo & Ricardo Campos & Manuel Galea, 2003. "Robust estimation of systematic risk using the t distribution in the chilean stock markets," Applied Economics Letters, Taylor & Francis Journals, vol. 10(7), pages 447-453.
    3. Antonio Sanhueza & Víctor Leiva & N. Balakrishnan, 2008. "A new class of inverse Gaussian type distributions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 68(1), pages 31-49, June.
    4. Filidor Labra & Reiko Aoki & Heleno Bolfarine, 2005. "Local influence in null intercept measurement error regression under a student_t model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(7), pages 723-740.
    5. Jose T.A.S. Ferreira & Mark F.J. Steel, 2004. "Bayesian Multivariate Regression Analysis with a New Class of Skewed Distributions," Econometrics 0403001, University Library of Munich, Germany.
    6. Griffin, J.E. & Steel, M.F.J., 2006. "Inference with non-Gaussian Ornstein-Uhlenbeck processes for stochastic volatility," Journal of Econometrics, Elsevier, vol. 134(2), pages 605-644, October.
    7. Felipe Osorio & Manuel Galea, 2006. "Detection of a change-point in student-t linear regression models," Statistical Papers, Springer, vol. 47(1), pages 31-48, January.
    8. Yongjae Kwon & Hamparsum Bozdogan & Halima Bensmail, 2009. "Performance of Model Selection Criteria in Bayesian Threshold VAR (TVAR) Models," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 83-101.

    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. Margarita Marín & Edilberto Cepeda-Cuervo, 2022. "A Bayesian Regression Model for the Non-standardized t Distribution with Location, Scale and Degrees of Freedom Parameters," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 809-830, November.
    2. Olawale Awe O. & Adedayo Adepoju A., 2018. "Modified Recursive Bayesian Algorithm For Estimating Time-Varying Parameters In Dynamic Linear Models," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 258-293, June.
    3. Justin L. Tobias & Mingliang Li, 2003. "A finite-sample hierarchical analysis of wage variation across public high schools: evidence from the NLSY and high school and beyond," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(3), pages 315-336.
    4. Chen, Cathy W.S. & Gerlach, Richard H. & Tai, Amanda P.J., 2008. "Testing for nonlinearity in mean and volatility for heteroskedastic models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 489-499.
    5. Wang, Yudong & Hao, Xianfeng, 2022. "Forecasting the real prices of crude oil: A robust weighted least squares approach," Energy Economics, Elsevier, vol. 116(C).
    6. Panagiotelis, Anastasios & Smith, Michael, 2010. "Bayesian skew selection for multivariate models," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1824-1839, July.
    7. Junrong Liu & Robin C. Sickles & E. G. Tsionas, 2017. "Bayesian Treatments for Panel Data Stochastic Frontier Models with Time Varying Heterogeneity," Econometrics, MDPI, vol. 5(3), pages 1-21, July.
    8. Markku Lanne & Arto Luoma & Jani Luoto, 2012. "Bayesian Model Selection And Forecasting In Noncausal Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 812-830, August.
    9. Miranowski, John A. & Monchuk, Daniel C., 2004. "Spatial Labor Markets and Technology Spillovers - Analysis from the US Midwest," Working Papers 18224, Iowa State University, Department of Economics.
    10. Haroon Mumtaz & Fulvia Marotta, 2023. "Vulnerability to Climate Change: Evidence from a Dynamic Factor Model," Working Papers 961, Queen Mary University of London, School of Economics and Finance.
    11. Doris A. Oberdabernig & Stefan Humer & Jesus Crespo Cuaresma, 2018. "Democracy, Geography and Model Uncertainty," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(2), pages 154-185, May.
    12. Moeltner, Klaus, 2019. "Bayesian nonlinear meta regression for benefit transfer," Journal of Environmental Economics and Management, Elsevier, vol. 93(C), pages 44-62.
    13. Fernández, C. & Steel, M.F.J., 1996. "On Bayesian Inference under Sampling from Scale Mixtures of Normals," Discussion Paper 1996-02, Tilburg University, Center for Economic Research.
    14. Susan L. Ettner & Betsy L. Cadwell & Louise B. Russell & Arleen Brown & Andrew J. Karter & Monika Safford & Carol Mangione & Gloria Beckles & William H. Herman & Theodore J. Thompson & and The TRIAD S, 2009. "Investing time in health: do socioeconomically disadvantaged patients spend more or less extra time on diabetes self‐care?," Health Economics, John Wiley & Sons, Ltd., vol. 18(6), pages 645-663, June.
    15. Bassetti, Federico & De Giuli, Maria Elena & Nicolino, Enrica & Tarantola, Claudia, 2018. "Multivariate dependence analysis via tree copula models: An application to one-year forward energy contracts," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1107-1121.
    16. Francesco Pattarin, 2018. "Spending Policies of Italian Banking Foundations," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0071, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    17. Vasco Cúrdia & Marco Del Negro & Daniel L. Greenwald, 2014. "Rare Shocks, Great Recessions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1031-1052, November.
    18. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676, July.
    19. Chan, Joshua C.C., 2021. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1212-1226.
    20. Fernández, C. & Steel, M.F.J., 1997. "On the Dangers of Modelling through Continuous Distributions : A Bayesian Perspective," Other publications TiSEM 53bef46d-6511-4d09-9018-d, Tilburg University, School of Economics and Management.

    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:tiu:tiutis:3fff240d-a587-4537-ba5f-22dcadd3f3b1. 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: Richard Broekman (email available below). General contact details of provider: https://www.tilburguniversity.edu/about/schools/economics-and-management/ .

    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.