Sequential Monte Carlo Template Class
smctc-100rc3.zip
smctc.pdfParticle Filter관련 자료를 검색하다가 찾은 사이트중 하나.
참고가 될것같아 올려둔다.
관련 URL : http://www2.warwick.ac.uk/fac/sci/statistics/staff/academic/johansen/smctc/
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 presented. Two example applications are provided: a simple particle filter for illustrative purposes and a state-of-the-art algorithm for rare event estimation.
This software is released under version 3 of the GNU General Public License.
Please be aware that this software is still in development, although all known bugs have been eliminated it is probable that some persist. If you wish to be added to a mailing list to receive information about updates to this software, then please send an email to the author, adam dot johansen at bristol dot ac dot uk. Otherwise, please check this page regularly for updates.
Downloads:
The library itself (presently version 1.00-RC3) is available in source format. It has been tested under a number of versions of Linux using GCC-3 and GCC-4, including Ubuntu, Gentoo and SuSe. It has also been successfully used under Windows, compiled using Microsoft Visual C++ 5 Express. It is also reported to work using Dev-C++ under windows.The software makes use of the GNU Scientific library, this is available from the main GNU software page. A Microsoft Visual C port in source and binary form can be found at David Geldreich's page. Guidelines on the use of GSL with Dev-C++ can be found at QuantCode.