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Improved power of one-sided tests

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  • Meyer, Mary C.
  • Wang, Jianqiang C.

Abstract

For the classical least-squares model it is often the case that shape or order restrictions are appropriate for the regression function, in the form of a set of linear inequality constraints imposed on the parameters. It is generally understood that the hypothesis test using the constrained alternative will provide higher power than the corresponding test using the unconstrained alternative. We present a formal proof that this is the case. Code for constrained estimation and testing is posted at www.stat.colostate.edu/~meyer/constrparam.htm.

Suggested Citation

  • Meyer, Mary C. & Wang, Jianqiang C., 2012. "Improved power of one-sided tests," Statistics & Probability Letters, Elsevier, vol. 82(8), pages 1619-1622.
    • Handle: RePEc:eee:stapro:v:82:y:2012:i:8:p:1619-1622
    DOI: 10.1016/j.spl.2012.04.016
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    References listed on IDEAS

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    1. Mary C. Meyer, 2003. "A test for linear versus convex regression function using shape-restricted regression," Biometrika, Biometrika Trust, vol. 90(1), pages 223-232, March.
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