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Testing equivalence to power law distributions

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  • Ostrovski, Vladimir

Abstract

We introduce a new test for equivalence to power law distributions. The test is based on the minimum distance method. The critical value can be calculated using the asymptotic approximation or can be estimated by bootstrapping. We apply the proposed test to two real data sets: the city sizes in Germany and the Open American National Corpus. The finite sample performance is studied by simulations, which are based on these real data sets.

Suggested Citation

  • Ostrovski, Vladimir, 2022. "Testing equivalence to power law distributions," Statistics & Probability Letters, Elsevier, vol. 181(C).
    • Handle: RePEc:eee:stapro:v:181:y:2022:i:c:s0167715221002492
    DOI: 10.1016/j.spl.2021.109287
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    References listed on IDEAS

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    1. Ostrovski, Vladimir, 2018. "Testing equivalence to families of multinomial distributions with application to the independence model," Statistics & Probability Letters, Elsevier, vol. 139(C), pages 61-66.
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    Cited by:

    1. D'Acci, Luca S., 2023. "Is housing price distribution across cities, scale invariant? Fractal distribution of settlements' house prices as signature of self-organized complexity," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).

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