In this thesis, we develop models to analyze zero-inflated truncated heavy-tailed dependent data to fit radio audience data in Switzerland. These models are able to explain, by means of covariates, both the probability of observing a positive outcome and the mean of the positive outcomes, which respectively correspond to the audience indicators of reach and of time spent listening. Estimation methods, model check, model assumptions and model properties are discussed. The fit of audience data for different Swiss radio stations in their broadcasting area are finally compared in order to select the process that best describes dependent daily listening times.