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On the correspondence between frequentist and Bayesian tests

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  • Ivair R. Silva

Abstract

Modern theory for statistical hypothesis testing can broadly be classified as Bayesian or frequentist. Unfortunately, one can reach divergent conclusions if Bayesian and frequentist approaches are applied in parallel to analyze the same data set. This is a serious impasse since there is a lack of consensus on when to use one approach in detriment of the other. However, this conflict can be resolved. The present paper shows the existence of a perfect equivalence between Bayesian and frequentist methods for testing. Hence, Bayesian and frequentist decision rules can always be calibrated, in both directions, in order to present concordant results.

Suggested Citation

  • Ivair R. Silva, 2018. "On the correspondence between frequentist and Bayesian tests," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(14), pages 3477-3487, July.
    • Handle: RePEc:taf:lstaxx:v:47:y:2018:i:14:p:3477-3487
    DOI: 10.1080/03610926.2017.1359296
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    Cited by:

    1. Marius-Ionuț Gordan & Elena Peț & Gabriela Popescu & Ioan Brad & Anda Ioana Milin & Tabita Cornelia Adamov & Ramona Ciolac & Anka Roxana Pascariu & Tiberiu Iancu, 2022. "Factors Influencing the Accommodation Prices of Romanian Rural Tourism," Sustainability, MDPI, vol. 15(1), pages 1-22, December.
    2. Fernández, Arturo J. & Correa-Álvarez, Cristian D. & Pericchi, Luis R., 2020. "Balancing producer and consumer risks in optimal attribute testing: A unified Bayesian/Frequentist design," European Journal of Operational Research, Elsevier, vol. 286(2), pages 576-587.

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