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Bayesian Inference for Linear Regression

Author

Listed:
  • Daniel Ciuiu

    (Technical University of Civil Engineering, Bucharest and Centre for macroeconomic Modelling, NIER, Romanian Academy)

Abstract

In this paper we will perform Bayesian inference for linear regression. The normal distribution case is considered, hence the distribution of the errors and the multivariate prior distribution of the coefficients are normal. From these we obtain a multivariate normal posterior distribution for the coefficients.

Suggested Citation

  • Daniel Ciuiu, 2017. "Bayesian Inference for Linear Regression," Working Papers of Macroeconomic Modelling Seminar 170803, Institute for Economic Forecasting.
    • Handle: RePEc:rjr:wpmems:170803
    as

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    File URL: http://www.ipe.ro/RePEc/WorkingPapers/cs28_1.pdf
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    References listed on IDEAS

    as
    1. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. Mr. Shaun K. Roache, 2010. "What Explains the Rise in Food Price Volatility?," IMF Working Papers 2010/129, International Monetary Fund.
    4. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    bayesian inference; linear regression;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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