Stability in Distribution of Randomly Perturbed Quadratic Maps as Markov Processes

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dc.creatorBhattacharya, Rabi
dc.creatorMajumdar, Mukul
dc.date2005-03-24
dc.date.accessioned2026-07-07T05:18:22Z
dc.date.available2026-07-07T05:18:22Z
dc.descriptionIteration of randomly chosen quadratic maps defines a Markov process: X_{n+1}=ε_{n+1}X_n(1-X_n), where ε_n are i.i.d. with values in the parameter space [0,4] of quadratic maps F_θ(x)=θx(1-x). Its study is of significance as an important Markov model, with applications to problems of optimization under uncertainty arising in economics. In this article a broad criterion is established for positive Harris recurrence of X_n.
dc.descriptionPublished at http://dx.doi.org/10.1214/105051604000000918 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0503540
dc.identifierhttp://arxiv.org/abs/math/0503540
dc.identifierAnnals of Applied Probability 2004, Vol. 14, No. 4, 1802-1809
dc.identifierdoi:10.1214/105051604000000918
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/74636
dc.subjectProbability
dc.subject60J05 (Primary) 60J20, 37H10. (Secondary)
dc.titleStability in Distribution of Randomly Perturbed Quadratic Maps as Markov Processes
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