This package implements the Sequential Monte Carlo "squared" (SMC^2) algorithm from Chopin, Jacob, and Papaspiliopoulos (2013). This algorithm allows sequential Bayesian inference of both latent variables and parameters in a general nonlinear statespace model. If only batch inference on model parameters is needed, there is also an implementation of the Densitytempered algorithm from Duan & Fulop (2015), which offers a more direct pathway from the prior to the posterior.
Package details 


Author  Derek Hansen 
Maintainer  Derek Hansen <[email protected]> 
License  GPL (>= 2) 
Version  0.01 
Package repository  View on GitHub 
Installation 
Install the latest version of this package by entering the following in R:

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