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New characterization-based exponentiality tests for randomly censored data

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Abstract

Recently, the characterization-based approach for the construction of goodness of fit tests has become popular. Most of the proposed tests have been designed for complete i.i.d. samples. Here, we present the adaptation of the recently proposed exponentiality tests based on equidistribution-type characterizations for the case of randomly censored data. Their asymptotic properties are provided. Besides, we present the results of wide empirical power study including the powers of several recent competitors. This study can be used as a benchmark for future tests proposed for this kind of data.

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Acknowledgements

We would like to thank the anonymous referees for their valuable remarks and suggestions that improved the paper.

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  1. Faculty of Mathematics, University of Belgrade, Belgrade, Serbia

    Marija Cuparić & Bojana Milošević

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  1. Marija Cuparić
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  2. Bojana Milošević
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Correspondence to Bojana Milošević.

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The work of M. Cuparić and B. Milošević is supported by the Ministry of Education, Science and Technological Development, Republic of Serbia, Serbia.

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Cuparić, M., Milošević, B. New characterization-based exponentiality tests for randomly censored data. TEST 31, 461–487 (2022). https://doi.org/10.1007/s11749-021-00787-7

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  • DOI: https://doi.org/10.1007/s11749-021-00787-7

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