Estimating Markov and semi-Markov switching linear mixed models with individual-wise random effects

Introduced in [7, 8], hidden Markov models formalise, among others, the idea that a dy- namical system evolves through its state space which is unknown to an observer or too

The Evidential EM (E2M) [5] is an interative algorithm dedicated to maximum likelihood estimation in statistical models based on uncertain observations encoded by belief

The underlying semi-Markov chain represents the succession of growth phases while the linear mixed models attached to each state of the underlying semi-Markov chain represent both

:فرﺎﻌﻤﻝا ﺞﻤد ،تﺎﻴﺎﻔﻜﻝا ﺎﻴﺠوﻏادﻴﺒ ﻲﻓ رﺼﺎﻨﻌﻝا مﻫأ نﻤ ﻲﻫو ﻲﻓ تﺎﻤوﻠﻌﻤﻝا ءﺎﻨﺒ وﺤﻨ مﻴﻠﻌﺘﻝا ﻪﻴﺠوﺘ مﺘﻴ ثﻴﺤ ﺞﻤدﻨﻤ رﺎطإ ، ،(داوﻤﻝا ﺔﻴﻝﻼﻘﺘﺴا) ﻲﻝازﻌﻨا لﻜﺸ ﻲﻓ سﻴﻝو

Figure 1 The hallmarks of cancer 21 Figure 2 The Ras GTPases cycle 22 Figure 3 Ras signaling network 23 Figure 4 The Ral GTPases cycle and Ral proteins 24 Figure 5

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des

L’établissement des semis de Pinus pinea a été étudié in situ et sous des conditions contrôlées pour trois forêts au nord de la Tunisie (Mekna III, Ouchtata II et

For the stopover duration application, the nonobserv- able Markov/semi-Markov model comprises three states: an initial transient Markovian state followed by a tran- sient