Bootstrap almost goodness-of-fit tests

A. Baíllo Moreno, J. Cárcamo Urtiaga

The almost goodness-of-fit test is a procedure to decide if a (parametric) model serves as a good representation of the probability distribution generating the sample. We use the M-estimator of the parameters to determine the approximating model (within the parametric class) to the unknown distribution. The main objective is the approximate validation of a distribution or an entire parametric family up to a pre-specified margin of error. The test statistic is the Lp-distance between the empirical distribution function and the corresponding one of the estimated (parametric) model. The rejection region is determined via an easy-to-implement and flexible bootstrap method.

Keywords: Bootstrap; Empirical process; Goodness-of-fit; Model validation

Scheduled

Non Parametric Statistics I
June 12, 2025  3:30 PM
Sala de prensa (MR 13)

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