Weighted (h,theta)-divergences in goodness-of-fit with composite null hypotheses

Abstract

Purpose - Proposes a test of goodness-of-fit with composite null hypotheses and weights in the classes based on weighted (h, p)-divergences. Design/methodology/approach - The weighted (h, p)-divergence between an empirical distribution and the probability of the estimated model is here investigated for large simple random samples.
Findings - The unknown parameters of the model are estimated using minimum (h, p)-divergences estimators with weights as studied in previous works by the authors.
Originality/value - Research makes an important contribution to (h, P)-divergences and their applications in statistical and other areas.