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A Comparison of Marginal Likelihood Based and Approximate Point Optimal Tests for Random Regression Coefficient in the Presence of Autocorrelation

Author

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  • Rahman, S.
  • King, M.L.

Abstract

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Suggested Citation

  • Rahman, S. & King, M.L., 1994. "A Comparison of Marginal Likelihood Based and Approximate Point Optimal Tests for Random Regression Coefficient in the Presence of Autocorrelation," Monash Econometrics and Business Statistics Working Papers 4/94, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:1994-4
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    Cited by:

    1. Sriananthakumar, Sivagowry & King, Maxwell L., 2006. "A new approximate point optimal test of a composite null hypothesis," Journal of Econometrics, Elsevier, vol. 130(1), pages 101-122, January.
    2. Jahar Bhowmik & Maxwell King, 2007. "Maximal invariant likelihood based testing of semi-linear models," Statistical Papers, Springer, vol. 48(3), pages 357-383, September.
    3. Sriananthakumar, Sivagowry, 2013. "Testing linear regression model with AR(1) errors against a first-order dynamic linear regression model with white noise errors: A point optimal testing approach," Economic Modelling, Elsevier, vol. 33(C), pages 126-136.
    4. Maxwell L. King & Sivagowry Sriananthakumar, 2015. "Point Optimal Testing: A Survey of the Post 1987 Literature," Monash Econometrics and Business Statistics Working Papers 5/15, Monash University, Department of Econometrics and Business Statistics.

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