首页 | 本学科首页   官方微博 | 高级检索  
     


Maximum likelihood estimator consistency for a ballistic random walk in a parametric random environment
Authors:Francis Comets  Mikael Falconnet  Oleg Loukianov  Dasha Loukianova  Catherine Matias
Affiliation:1. Laboratoire Probabilités et Modèles Aléatoires, Université Paris Diderot, UMR CNRS 7599, France;2. Laboratoire Statistique et Génome, Université d’Évry Val d’Essonne, UMR CNRS 8071, USC INRA, France;3. Département Informatique, IUT de Fontainebleau, Université Paris Est, France;4. Laboratoire Analyse et Probabilités, Université d’Évry Val d’Essonne, France
Abstract:We consider a one dimensional ballistic random walk evolving in an i.i.d. parametric random environment. We provide a maximum likelihood estimation procedure of the parameters based on a single observation of the path till the time it reaches a distant site, and prove that the estimator is consistent as the distant site tends to infinity. Our main tool consists in using the link between random walks and branching processes in random environments and explicitly characterising the limiting distribution of the process that arises. We also explore the numerical performance of our estimation procedure.
Keywords:62M05   62F12   60J25
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号