Nonparametric estimation of the chaotic function and the invariant measure of a dynamical system
D. Bosq and
D. Guégan
Statistics & Probability Letters, 1995, vol. 25, issue 3, 201-212
Abstract:
Let (Xt), be valued stochastic process defined by a discrete time dynamical system as Xt = [phi](Xt-1, T = 1,2,..., where [phi] is some nonlinear function preserving a probability measure say [mu], we estimate [phi] and the density -f of [mu] without using special condition on the analytical form of [phi], with nonparametric methods and some convergence rates are given.
Date: 1995
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0167-7152(94)00223-U
Full text for ScienceDirect subscribers only
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:eee:stapro:v:25:y:1995:i:3:p:201-212
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
Access Statistics for this article
Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul
More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().