dereklh24/RSMC2: Bayesian estimation of non-linear state-space models

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.

Getting started

Package details

AuthorDerek Hansen
MaintainerDerek Hansen <derek.l.hansen@gmail.com>
LicenseGPL (>= 2)
Version0.01
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("dereklh24/RSMC2")
dereklh24/RSMC2 documentation built on Nov. 6, 2019, 2:53 a.m.