Fractional ARIMA (and Other Long Memory) Time Series Modeling

Simulates, fits, and predicts long-memory and anti-persistent time series, possibly mixed with ARMA, regression, transfer-function components. Exact methods (MLE, forecasting, simulation) are used. Bug reports should be done via GitHub (at <>), where the development version of this package lives; it can be installed using devtools.

An R time series library that mixes arima models with 3 types of long-memory processes: FDWN, FGN, and PLA (power-law autocovariance.)


Reference manual

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1.7-0 by JQ Veenstra, 3 years ago

Browse source code at

Authors: JQ (Justin) Veenstra [aut, cre] , A.I. McLeod [aut]

Documentation:   PDF Manual  

Task views: Time Series Analysis

MIT + file LICENSE license

Imports parallel

Depends on ltsa

Imported by tscopula.

Suggested by iAR.

See at CRAN