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Introduction
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What is a model? A joint probability distribution!
Description, representation & implementation of a model
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Modeling the individual parameters
Modeling the observations
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The SAEM algorithm for estimating population parameters
The Metropolis-Hastings algorithm for simulating the individual parameters
Estimation of the observed Fisher information matrix
Estimation of the log-likelihood
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