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Rank tests and regression rank score tests in measurement error models

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  • Jurecková, Jana
  • Picek, Jan
  • Saleh, A.K.Md. Ehsanes

Abstract

The rank and regression rank score tests of linear hypothesis in the linear regression model are modified for measurement error models. The modified tests are still distribution free. Some tests of linear subhypotheses are invariant to the nuisance parameter, others are based on the aligned ranks using the R-estimators. The asymptotic relative efficiencies of tests with respect to tests in models without measurement errors are evaluated. The simulation study illustrates the powers of the tests.

Suggested Citation

  • Jurecková, Jana & Picek, Jan & Saleh, A.K.Md. Ehsanes, 2010. "Rank tests and regression rank score tests in measurement error models," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3108-3120, December.
    • Handle: RePEc:eee:csdana:v:54:y:2010:i:12:p:3108-3120
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    References listed on IDEAS

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    Cited by:

    1. Saleh, A.K.Md. Ehsanes & Shalabh,, 2014. "A ridge regression estimation approach to the measurement error model," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 68-84.
    2. A. Saleh & Jan Picek & Jan Kalina, 2012. "R-estimation of the parameters of a multiple regression model with measurement errors," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(3), pages 311-328, April.

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