R: Simulates, fits, and predicts persistent and anti-persistent...
arfima-package
R Documentation
Simulates, fits, and predicts persistent and anti-persistent time series.
arfima
Description
Simulates with arfima.sim, fits with arfima, and predicts with a method for the generic function. Plots predictions and the original time series.
Has the capability to fit regressions with ARFIMA/ARIMA-FGN/ARIMA-PLA errors, as well as transfer functions/dynamic regression.
Details
Package:
arfima
Type:
Package
Version:
1.3-0
Date:
2015-12-10
License:
GPL (>= 2)
A list of functions:
arfima.sim - Simulates an ARFIMA, ARIMA-FGN, or ARIMA-PLA (three classes of mixed ARIMA hyperbolic decay processes) process, with possible seasonal components.
arfima - Fits an ARIMA-HD (multi-start) model to a series, with options for regression with ARIMA-HD errors and dynamic regression (transfer functions). Allows for fixed parameters as well as choices for the optimizer to be used.
arfima0 - Simplified version of arfima
weed - Weeds out modes too close to each other in the same fit. The modes with the highest log-likelihoods are kept
print.arfima - Prints the relevant output of an arfima fitted object, such as parameter estimates, standard errors, etc.
summary.arfima - A much more detailed version of print.arfima
coef.arfima - Extracts the coefficients from a arfima object
vcov.arfima - Theoretical and observed covariance matrices of the coefficients
residuals.arfima - Extracts the residuals or regression residuals from a arfima object
fitted.arfima - Extracts the fitted values from a arfima object
Boot and Boot.arfima - Computes (a) parametric bootstrap replicate(s) from the fitted arfima object. Boot is a generic function while Boot.arfima is the method for arfima objects.
tacvfARFIMA - Computes the theoretical autocovariance function of a supplied model. The model is checked for stationarity and invertibility.
iARFIMA - Computes the Fisher information matrix of all non-FGN components of the given model. Can be computed (almost) exactly or through a psi-weights approximation. The approximation takes more time.
IdentInvertQ - Checks whether the model is identifiable, stationary, and invertible. Identifiability is checked through the information matrix of all non-FGN components, as well as whether both types of fractional noise are present, both seasonally and non-seasonally.
lARFIMA and lARFIMAwTF - Computes the log-likelihood of a given model with a given series. The second admits transfer function data.
predict.arfima - Predicts from an arfima object. Capable of exact minimum mean squared error predictions even with integer d > 0 and/or integer dseas > 0. Does not include transfer function/leading indicators as of yet. Returns a predarfima object, which is composed of: predictions, standard errors (exact and, if possible, limiting), as well as parametric bootstrap prediction intervals and predictions if requested.
print.predarfima - Prints the relevant output from a predarfima object: the predictions, their standard deviations, and if part of the object, the lower and upper bootstrap prediction intervals.
plot.predarfima - Plots a predarfima object. This includes the original time series, the forecasts, the standard 95% prediction intervals (exact and, if available, limiting) as well as the bootstrap lower and upper intervals and predictions.
logLik.arfima, AIC.arfima, BIC.arfima - Extracts the requested values from an arfima object
distance - Calculates the distances between the modes
removeMode - Removes a mode from a fit
tacvf - Calculates the theoretical autocovariance functions (tacvfs) from a fitted arfima object
plot.tacvf - Plots the tacvfs
print.tacvf - Prints the tacvfs
tacfplot - Plots the theoretical autocorrelation functions (tacfs) of different models on the same data
SeriesJ, tmpyr - Two datasets included with the package
Author(s)
Justin Veenstra, A. I. McLeod
Maintainer: A. I. McLeod <aimcleod@uwo.ca>
References
Veenstra, J. and McLeod, A. I. (Working Paper).
The arfima R package: Exact Methods for Hyperbolic Decay Time Series