Rayleigh model fitting to nonnegative discrete data

The paper deals with modeling ordinal discrete random variables with a high number of nonnegative realizations. The prediction of the Rayleigh distribution learned on clusters of the explanatory variables is proposed. The proposed solution consists of the clustering and estimation phases based on the knowledge both of the target and explanatory variables, and the prediction phase using only the information from the explanatory variables. The main contributions of the approach are: (i) using the discretized knowledge of clusters of the explanatory variables and (ii) describing nonnegative discrete data by the multimodal Rayleigh distribution. Experiments with a data set from a tram network are provided.