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Robust Model Selection for Stochastic Processes

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Author(s):
Garcia, Jesus E. ; Gonzalez-Lopez, V. A. ; Viola, M. L. L.
Total Authors: 3
Document type: Journal article
Source: COMMUNICATIONS IN STATISTICS-THEORY AND METHODS; v. 43, n. 10-12, p. 11-pg., 2014-05-15.
Abstract

We address the problem of robust model selection for finite memory stochastic processes. Consider m independent samples, with most of them being realizations of the same stochastic process with law Q, which is the one we want to retrieve. We define the asymptotic breakdown point for a model selection procedure and also we devise a model selection procedure. We compute the value of which is 0.5, when all the processes are Markovian. This result is valid for any family of finite order Markov models but for simplicity we will focus on the family of variable length Markov chains. (AU)

FAPESP's process: 13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat
Grantee:Oswaldo Baffa Filho
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 12/06078-9 - Portuguese in time and space: linguistic contact, grammars in competition and parametric change
Grantee:Charlotte Marie Chambelland Galves
Support Opportunities: Research Projects - Thematic Grants