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 non-linear state-space model. If only batch inference on model parameters is needed, there is also an implementation of the Density-tempered 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 <derek.l.hansen@gmail.com> |
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:
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.