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
Auditorio 1. Ricard Vinyes


Other papers in the same session


Cookie policy

We use cookies in order to be able to identify and authenticate you on the website. They are necessary for the correct functioning of it, and therefore they can not be disabled. If you continue browsing the website, you are agreeing with their acceptance, as well as our Privacy Policy.

Additionally, we use Google Analytics in order to analyze the website traffic. They also use cookies and you can accept or refuse them with the buttons below.

You can read more details about our Cookie Policy and our Privacy Policy.