Simultaneously Modelling Occurrence and Quantity of Multivariate Semicontinuous Data

Joint models have been developed recently for multivariate semicontinuous data; however, joint modelling implies structured covariance and nonnegative correlation among responses, and thus is inflexible in accommodating complex covariance structures in practice. In addition, zero‐inflated continuous data have been traditionally handled by two‐part mixed models where zero and positive responses are analysed separately; therefore, the multivariate nature of the data would be destroyed. In this paper, we introduce a new model for multivariate semicontinuous data by incorporating distribution‐free multivariate random effects of unstructured covariance into Tweedie compound Poisson regression model. An optimal estimation of our model has been developed using the orthodox best linear unbiased predictors of multivariate random effects. Our method is illustrated through the analysis of Mali family farmer data.