This paper develops a class of models to deal with missing data from longitudinal studies. We assume that separate models for the primary response and missingness (e.g., number of missed visits) are ...

The issues of model-based clustering and classification of longitudinal data have received increasing attention in recent years. In this paper, we propose a finite mixture of multivariate t linear ...

The standard linear regression model does not apply when the effect of one explanatory variable on the dependent variable depends on the value of another explanatory variable. In this case, the ...

In the modern field of deep learning, linear attention mechanisms are gradually becoming a powerful tool for handling long sequence data. Recent research has revealed how these mechanisms 'decay' ...