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A Robust Test for Non‐nested Hypotheses

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  • Maria‐Pia Victoria‐Feser

Abstract

We propose a robust version of Cox‐type test statistics for the choice between two non‐nested hypotheses. We first show that the influence of small amounts of contamination in the data on the test decision can be very large. Secondly, we build a robust test statistic by using the results on robust parametric tests that are available in the literature and show that the level of the robust test is stable. Finally, we show numerically not only the robustness of this new test statistic but also that its asymptotic distribution is a good approximation of its sample distribution, unlike for the classical test statistic. We apply our results to the choice between a Pareto and an exponential distribution as well as between two competing regressors in the simple linear regression model without intercept.

Suggested Citation

  • Maria‐Pia Victoria‐Feser, 1997. "A Robust Test for Non‐nested Hypotheses," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(3), pages 715-727.
    • Handle: RePEc:bla:jorssb:v:59:y:1997:i:3:p:715-727
    DOI: 10.1111/1467-9868.00093
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