A distribuição gama inversa com zeros ajustados

Abstract

In this work, we introduce a new class of semi-continuous distributions, composed of the inverse gamma distribution as the continuous component and a Bernoulli distribution as the discrete component. We explore various properties of this distribution, including presenting novel results, and derive the maximum likelihood estimators. Additionally, we conduct simulation studies to assess the performance of the proposed estimators in different scenarios, where precision varies and zero proportions differ. Finally, we provide an example with real data in which the proposed distribution demonstrates a superior fit compared to the gamma distribution with adjusted zeros.