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- W3100298023 abstract "The Hurst exponent is the simplest numerical summary of self-similar long-range dependent stochastic processes. We consider the estimation of Hurst exponent in long-range dependent curve time series. Our estimation method begins by constructing an estimate of the long-run covariance function, which we use, via dynamic functional principal component analysis, in estimating the orthonormal functions spanning the dominant sub-space of functional time series. Within the context of functional autoregressive fractionally integrated moving average models, we compare finite-sample bias, variance and mean square error among some time- and frequency-domain Hurst exponent estimators and make our recommendations." @default.
- W3100298023 created "2020-11-23" @default.
- W3100298023 creator A5087947210 @default.
- W3100298023 date "2020-01-02" @default.
- W3100298023 modified "2023-09-23" @default.
- W3100298023 title "A Comparison of Hurst Exponent Estimators in Long-range Dependent Curve Time Series" @default.
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- W3100298023 doi "https://doi.org/10.1515/jtse-2019-0009" @default.
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