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A classical problem in linear regression or how to estimate the mean of a univariate normal distribution with known variance

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  • Magnus, J.R.

    (Tilburg University, Center For Economic Research)

  • Durbin, J.

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Suggested Citation

  • Magnus, J.R. & Durbin, J., 1996. "A classical problem in linear regression or how to estimate the mean of a univariate normal distribution with known variance," Discussion Paper 1996-60, Tilburg University, Center for Economic Research.
    • Handle: RePEc:tiu:tiucen:325b330c-b816-4978-90c2-5ef317bcc75e
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    References listed on IDEAS

    as
    1. Leamer, Edward E, 1992. "Bayesian Elicitation Diagnostics," Econometrica, Econometric Society, vol. 60(4), pages 919-942, July.
    2. Karim Abadir, 1999. "An introduction to hypergeometric functions for economists," Econometric Reviews, Taylor & Francis Journals, vol. 18(3), pages 287-330.
    3. McAleer, Michael & Pagan, Adrian R & Volker, Paul A, 1985. "What Will Take the Con out of Econometrics?," American Economic Review, American Economic Association, vol. 75(3), pages 293-307, June.
    4. Giles, D. E. A. & Rayner, A. C., 1979. "The mean squared errors of the maximum likelihood and natural-conjugate bayes regression estimators," Journal of Econometrics, Elsevier, vol. 11(2-3), pages 319-334.
    5. Feldstein, Martin S, 1973. "Multicollinearity and the Mean Square Error of Alternative Estimators," Econometrica, Econometric Society, vol. 41(2), pages 337-346, March.
    6. Farebrother, R W, 1975. "Minimax Regret Significance Points for a Preliminary Test in Regression Analysis: Comment," Econometrica, Econometric Society, vol. 43(5-6), pages 1005-1006, Sept.-Nov.
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