pmhtutorial: Minimal Working Examples for Particle Metropolis-Hastings
Routines for state estimate in a linear
Gaussian state space model and a simple stochastic volatility model using
particle filtering. Parameter inference is also carried out in these models
using the particle Metropolis-Hastings algorithm that includes the particle
filter to provided an unbiased estimator of the likelihood. This package is
a collection of minimal working examples of these algorithms and is only
meant for educational use and as a start for learning to them on your own.
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