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Deformetrica implements three estimation methods for minimizing the loss functions of the different models: a simple **gradient ascent**, the **L-BFGS algorithm** from [SciPy.org](https://docs.scipy.org/doc/scipy/reference/optimize.minimize-lbfgsb.html), and a stochastic version of the EM algorithm (still unstable).
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In general, we advise the use of the `ScipyLBFGS` estimator, which converges faster. The `GradientAscent` estimator might prove more robust in some situations.
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In general, we advise the use of the `ScipyLBFGS` estimator, which converges faster. The `GradientAscent` estimator might prove more robust in some situations, and is chosen by default for this reason.
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The `McmcSaem` estimator can only be used with the bayesian and longitudinal atlas. This algorithm is still under development, its full support with the bayesian atlas is scheduled for Deformetrica 4.1.0. |
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