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.
|Date of publication||2017-10-07 14:34:07 UTC|
|Maintainer||Johan Dahlin <[email protected]>|
|Package repository||View on CRAN|
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