Facolta’ di Scienze
Dipartimento di Matematica e Informatica
Martedì 2 febbraio dalle ore 17:00,
Summary. In this talk we present a series of goodness-of-fit tests for the family of skew-normal models when all parameters are unknown. As the null distributions of the considered test statistics depend only on asymmetry parameter, we used a default and proper prior on skewness parameter leading to the prior predictive p-value advocated by G. Box. Goodness-of-fit tests, here proposed, depend only on sample size and exhibit full agreement between nominal and actual size. They also have good power against local alternative models which also account for asymmetry in data. We illustrate how to use our procedure to check the GOF of the SN model to two applications: Frontier data and biomedical measurements, using the R package GOFSN. More details in Cabras, S. and Castellanos M.E. Journal of Applied Statistics, 36, (2), 223-232.
Per ulteriori informazioni contattare:
Stefano Cabras
Dipartimento di Matematica e Informatica
Via Ospedale, 72 (+39 070/6758516)