Data processing and source identification using lower dimensional hidden structure plays an essential role in many fields of applications, including image processing, neural networks, genome studies, signal processing and other areas where large datasets are often encountered. One of the common...

The semiparametric accelerated hazards mixture cure model provides a useful alternative to analyze survival data with a cure fraction if covariates of interest have a gradual effect on the hazard of uncured patients. However, the application of the model may be hindered by the computational...

In this work we propose a novel EM method for the estimation of nonlinear nonparametric mixed-effects models, aimed at unsupervised classification. We perform simulation studies in order to evaluate the algorithm performance and we apply this new procedure to a real dataset. Copyright...

Nonlinear state space models with mixed-effect (NLMESSM) are proposed to model HIV clinical longitudinal data. With NLMESSM, filtering algorithms are proposed to estimate the individual/population states. Maximum likelihood via iterated filtering and variance components model are proposed to...