Perfect Simulation and Convex Mixture of Context Trees
Nancy L. Garcia () and
Sandro Gallo ()
Additional contact information
Nancy L. Garcia: University of Campinas, Institute of Mathematics, Statistics and Scientific Computing
Sandro Gallo: Federal University of São Carlos, Center of Sciences
A chapter in Advances in Mathematics and Applications, 2018, pp 153-178 from Springer
Abstract:
Abstract Chains with unbounded memory have attracted lot of attention since the 30s and the pioneering work of Onicescu and Mihoc (Bull Sci Math 59(2):174–192, 1935) and Doeblin and Fortet (Bull Soc Math France 65:132–148, 1937). The construction of perfect simulation algorithm for these chains was first presented in the beginning of the century, and the particular case of discontinuous cases was first studied in the 2010s. The present paper presents a particular approach to perfect simulation of possibly discontinuous chains with unbounded memory. The main idea is to use a representation of the kernel through a convex mixture of probabilistic context trees.
Date: 2018
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-94015-1_7
Ordering information: This item can be ordered from
http://www.springer.com/9783319940151
DOI: 10.1007/978-3-319-94015-1_7
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().