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Conference Papers Year : 2008

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

Abstract

We address the estimation of Markov (and semi-Markov) switching linear mixed models i.e. models that combine linear mixed models with individual-wise random effects in a (semi-)Markovian manner. A MCEM-like algorithm whose iterations decompose into three steps (sampling of state sequences given random effects, prediction of random effects given the state sequence and maximization) is proposed. This statistical modeling approach is illustrated by the analysis of successive annual shoots along Corsican pine trunks.
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Dates and versions

hal-00831807 , version 1 (07-06-2013)

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  • HAL Id : hal-00831807 , version 1

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Florence Chaubert-Pereira, Yann Guédon, Christian Lavergne, Catherine Trottier. Estimating Markov and semi-Markov switching linear mixed models with individual-wise random effects. Computational Statistics, COMPSTAT'2008, 18th Symposium of IASC, 2008, Porto, Portugal. pp.11-18. ⟨hal-00831807⟩
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