On the use of priors in goodness-of-fit tests

Priors are introduced into goodness-of-fit tests, both for unknown parameters in the tested distribution and on the alternative density. Neyman–Pearson theory leads to the test with the highest expected power. To make the test practical, we seek priors that make it likely a priori that the power wil...

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Veröffentlicht in:	Canadian journal of statistics 2019-12, Vol.47 (4), p.560-579
Hauptverfasser:	CONTRERAS-CRISTÁN, Alberto, LOCKHART, Richard A., STEPHENS, Michael A., SUN, Shaun Z.
Format:	Artikel
Sprache:	eng
Schlagworte:	Alternatives Approximation Cramér–von Mises tests Density Dirichlet process Gaussian process Mathematical analysis Neyman–Pearson lemma Null hypothesis Parameters Power prior distributions Statistical analysis Uniform distribution
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