Zero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distance

Eduardo de Freitas Costa*, Silvana Schneider, Giulia Bagatini Carlotto, Tainá Cabalheiro, Mauro Ribeiro de Oliveira Júnior

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)


The dynamics of the wild boar population has become a pressing issue not only for ecological purposes, but also for agricultural and livestock production. The data related to the wild boar dispersal distance can have a complex structure, including excess of zeros and right-censored observations, thus being challenging for modeling. In this sense, we propose two different zero-inflated-right-censored regression models, assuming Weibull and gamma distributions. First, we present the construction of the likelihood function, and then, we apply both models to simulated datasets, demonstrating that both regression models behave well. The simulation results point to the consistency and asymptotic unbiasedness of the developed methods. Afterwards, we adjusted both models to a simulated dataset of wild boar dispersal, including excess of zeros, right-censored observations, and two covariates: age and sex. We showed that the models were useful to extract inferences about the wild boar dispersal, correctly describing the data mimicking a situation where males disperse more than females, and age has a positive effect on the dispersal of the wild boars. These results are useful to overcome some limitations regarding inferences in zero-inflated-right-censored datasets, especially concerning the wild boar’s population. Users will be provided with an R function to run the proposed models.

Original languageEnglish
Pages (from-to)1133-1155
JournalJapanese Journal of Statistics and Data Science
Issue number2
Early online date15 May 2021
Publication statusPublished - 2021


  • Censored data
  • Dispersal
  • Distance
  • Wild boar
  • Zero-inflated data


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