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We address regularised versions of the Expectation-Maximisation (EM)algorithm for Generalised Linear Mixed Models (GLMM) in the context of paneldata (measured on several individuals at different time points). A randomresponse y is modelled by a GLMM, using a set X of explanatory variables andtwo random effects. The first effect introduces the dependence withinindividuals on which data is repeatedly collected while the second embodies theserially correlated time-specific effect shared by all the individuals.Variables in X are assumed many and redundant, so that regression demandsregularisation. In this context, we first propose a L2-penalised EM algorithmfor low-dimensional data, and then a supervised component-based regularised EMalgorithm for the high-dimensional case.

R\'egularisation dans les Mod\`eles Lin\'eaires G\'en\'eralis\'es Mixtes avec effet al\'eatoire autor\'egressif