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Hyperbolic Decay Time Series

A. Ian McLeod
Organization: University of Western Ontario
Department: Department of Statistical and Actuarial Sciences
URL: http://www.stats.uwo.ca/faculty/aim/
Journal / Anthology

accepted for publication in The Journal of Time Series Analysis
Year: 1997

Hyperbolic decay time series such as, fractional Gaussian noise (FGN) or fractional autoregressive moving-average (FARMA) process, each exhibit two distinct types of behavior: strong persistence or antipersistence. Beran (1994) characterized the family of strongly persistent time series. A more general family of hyperbolic decay time series is introduced and its basic properties are characterized in terms of the autocovariance and spectral density functions. The random shock and inverted form representations are derived. It is shown that every strongly persistent series is the dual of an antipersistent series and vice versa. The asymptotic generalized variance of hyperbolic decay time series with unit innovation variance is shown to be infinite which implies that the variance of the minimum mean-square error one-step linear predictor using the last k observations decay slowly to the innovation variance as k gets large.

*Mathematics > Probability and Statistics

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