New robust confidence intervals for the mean under dependence

The goal of this paper is to indicate a new method for constructing normal confidence intervals for the mean, when the data is coming from stochastic structures with possibly long memory, especially when the dependence structure is not known or even the existence of the density function. More precis...

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Bibliographic Details
Published in:arXiv.org 2017-12
Main Authors: Longla, Martial, Peligrad, Magda
Format: Article
Language:English
Subjects:
Confidence intervals
Dependence
Markov chains
Statistical analysis
Online Access:Get full text
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Summary:The goal of this paper is to indicate a new method for constructing normal confidence intervals for the mean, when the data is coming from stochastic structures with possibly long memory, especially when the dependence structure is not known or even the existence of the density function. More precisely we introduce a random smoothing suggested by the kernel estimators for the regression function. Applications are presented to linear processes and reversible Markov chains with long memory.
ISSN:2331-8422