Confidence intervals for the Hurst parameter of a fractional Brownian motion based on finite sample size
classification
🧮 math.ST
stat.TH
keywords
brownianfractionalmotionintervalsparameterconfidencehurstsample
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In this paper, we show how concentration inequalities for Gaussian quadratic form can be used to propose exact confidence intervals of the Hurst index parametrizing a fractional Brownian motion. Both cases where the scaling parameter of the fractional Brownian motion is known or unknown are investigated. These intervals are obtained by observing a single discretized sample path of a fractional Brownian motion and without any assumption on the parameter $H$.
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