Posts tagged DEMetropolis(Z)

DEMetropolis(Z) Sampler Tuning

For continuous variables, the default PyMC sampler (NUTS) requires that gradients are computed, which PyMC does through autodifferentiation. However, in some cases, a PyMC model may not be supplied with gradients (for example, by evaluating a numerical model outside of PyMC) and an alternative sampler is necessary. The DEMetropolisZ sampler is an efficient choice for gradient-free inference. The implementation of DEMetropolisZ in PyMC is based on ter Braak and Vrugt [2008] but with a modified tuning scheme. This notebook compares various tuning parameter settings for the sampler, including the drop_tune_fraction parameter which was introduced in PyMC.

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