Parallel Sequential Monte Carlo for Efficient Density Combination: The DeCo MATLAB Toolbox
Stefano Grassi (),
Francesco Ravazzolo () and
Herman van Dijk
Journal of Statistical Software, 2015, vol. 068, issue i03
This paper presents the MATLAB package DeCo (density combination) which is based on the paper by Billio, Casarin, Ravazzolo, and van Dijk (2013) where a constructive Bayesian approach is presented for combining predictive densities originating from different models or other sources of information. The combination weights are time-varying and may depend on past predictive forecasting performances and other learning mechanisms. The core algorithm is the function DeCo which applies banks of parallel sequential Monte Carlo algorithms to filter the time-varying combination weights. The DeCo procedure has been implemented both for standard CPU computing and for graphical process unit (GPU) parallel computing. For the GPU implementation we use the MATLAB parallel computing toolbox and show how to use general purpose GPU computing almost effortlessly. This GPU implementation provides a speed-up of the execution time of up to seventy times on a standard CPU MATLAB implementation on a multicore CPU. We show the use of the package and the computational gain of the GPU version through some simulation experiments and empirical applications.
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8) Track citations by RSS feed
Downloads: (external link)
https://www.jstatsoft.org/index.php/jss/article/do ... ile/v068i03/DeCo.zip
https://www.jstatsoft.org/index.php/jss/article/do ... 8i03-replication.zip
Working Paper: Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox (2015)
Working Paper: Parallel sequential Monte Carlo for efficient density combination: The DeCo MATLAB toolbox (2014)
Working Paper: Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox (2013)
Working Paper: Parallel Sequential Monte Carlo for Efficient Density Combination: The DeCo Matlab Toolbox (2013)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:068:i03
Access Statistics for this article
Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis
More articles in Journal of Statistical Software from Foundation for Open Access Statistics
Bibliographic data for series maintained by Christopher F. Baum ().