The class of CUB models is commonly used by practitioners to model ordinal data, in this paper we propose the cubm package which provides the class of CUB models in the R system for statistical computing. The cubm package allows to specify a formula for each parameter of the model, the Maximum Likelihood (ML) estimation is performed by optimization via the functions nlminb, optim and DEoptim and the variance-covariance matrix can be obtained by numerical approximation of the Hessian matrix or by bootstrap method. The utility of the package is illustrated by an application and a simulation study.

In this paper, we present an application of GAMLSS (Generalized Additive Models for Location, Shape and Scale) to study bacterial cellulose production from agro-industrial waste. An experiment was conducted to research the effects of pH and cultivation time on bacterial cellulose yield obtained from discarded bananas. Several models were fitted to the collected data to determine an estimated expression for the mean and variance of bacterial cellulose yield. We found that the mean and variance of cellulose yield decrease as pH increases, while the opposite occurs as cultivation time increases.