Welcome to the RcppSMC documentation!
Sequential Monte Carlo methods are a very general class of Monte Carlo methods for sampling from sequences of distributions. Simple examples of these algorithms (often termed particle filters) are used very widely in the tracking and signal processing literature. Recent developments illustrate that these techniques have much more general applicability, and can be applied very effectively to statistical inference problems. Unfortunately, these methods are often perceived as being computationally expensive and difficult to implement. This library seeks to address both of these problems.
A C++ template class library for the efficient and convenient implementation of very general Sequential Monte Carlo algorithms (or general particle interpretations of Feynman-Kac formulae) is embedded inside R. Various examples illustrate the flexibility of algorithms that can be implemented this way.
This software is released under version 3 of the GNU General Public License . Please be aware that this software is still in development, and although all known bugs have been eliminated it is possible that some persist. Please check the project development sources on Github for the most recent version and important updates.