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arfima

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

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Install

install.packages('arfima')

Monthly Downloads

825

Version

1.8-1

License

MIT + file LICENSE

Maintainer

JQ (Justin) Veenstra

Last Published

August 19th, 2022

Functions in arfima (1.8-1)

Exact MLE for ARFIMA The time series is corrected for the sample mean and then exact MLE is used for the other parameters. This is a simplified version of the arfima() function that may be useful in simulations and bootstrapping.

Simulate an ARFIMA time series.

Prints changes to the package since the last update. Started in 1.4-0

Information criteria for arfima objects

The distance between modes of an arfima fit.

Exact log-likelihood of a long memory model with a transfer function model and series included Computes the exact log-likelihood of a long memory model with respect to a given time series as well as a transfer fucntion model and series. This function is not meant to be used directly.

Extract Model Fitted Values

Extract Log-Likelihood Values

residuals.arfima

Extract the Residuals of a Fitted Object

Finds the best modes of an arfima fit.

Checks invertibility, stationarity, and identifiability of a given set of parameters

sim_from_fitted

Simulate an ARFIMA time series from a fitted arfima object.

Converts AR/MA coefficients from the PACF space to operator space

Prints a tacvf object.

Predicts from a fitted object.

Exact log-likelihood of a long memory model

Converts AR/MA coefficients from operator space to the PACF space

Extract Model Coefficients

Removes a mode from an arfima fit.

Prints a Fitted Object

Temperature Data

Weeds out fits from a call to arfima that are too close to each other.

Plots the theoretical autocorralation functions (tacfs) of one or more fits.

Extracts the Variance-Covariance Matrix

Extensive Summary of an Object

The Fisher information matrix of an ARFIMA process

print.predarfima

Prints predictions and prediction intervals

Series J, Gas Furnace Data

print.summary.arfima

Prints the output of a call to summary on an arfima object

Simulates, fits, and predicts persistent and anti-persistent time series. arfima

Plots the output from a call to tacvf

plot.predarfima

Plots the original time series, the predictions, and the prediction intervals for a predarfima object.

Extracts the tacvfs of a fitted object

The theoretical autocovariance function of a long memory process.

Fit ARFIMA, ARIMA-FGN, and ARIMA-PLA (multi-start) models Fits ARFIMA/ARIMA-FGN/ARIMA-PLA multi-start models to times series data. Options include fixing parameters, whether or not to fit fractional noise, what type of fractional noise (fractional Gaussian noise (FGN), fractionally differenced white noise (FDWN), or the newly introduced power-law autocovariance noise (PLA)), etc. This function can fit regressions with ARFIMA/ARIMA-FGN/ARIMA-PLA errors via the xreg argument, including dynamic regression (transfer functions).