GetFitARMA: Fit ARMA(p,q) model to mean zero time series.

In FitARMA: Fit ARMA or ARIMA Using Fast MLE Algorithm

Description

The algorithm of McLeod and Zhang (2007) is used.

Usage

GetFitARMA(y, p, q, pApprox = 30, init = 0)

Arguments

y	time series
p	AR order
q	MA order
pApprox	AR approximation
init	initial parameter estimates

Details

See McLeod and Zhang (2006).

Value

loglikelihood	value of maximized loglikelihood
phiHat	estimated phi parameters
thetaHat	estimated theta parameters
convergence	result from optim
algorithm	indicates "L-BFGS-B" or "Nelder-Mead" according as which algorithm was used in optim

Author(s)

A.I. McLeod, [e-mail]

References

A.I. McLeod andY. Zhang (2008), Faster ARMA maximum likelihood estimation, Computational Statistics & Data Analysis, 52-4, 2166-2176. DOI link: http://dx.doi.org/10.1016/j.csda.2007.07.020

See Also

arima, FitARMA

Examples

data(SeriesA)
z<-SeriesA-mean(SeriesA)
GetFitARMA(z, 1, 1)
w<-diff(z, differences=1)
GetFitARMA(w, 0, 1)

Example output

Loading required package: FitAR
Loading required package: lattice
Loading required package: leaps
Loading required package: ltsa
Loading required package: bestglm
$loglikelihood
[1] 228.7854

$phiHat
[1] 0.9086651

$thetaHat
[1] 0.5758

$convergence
[1] 0

$algorithm
[1] "L-BFGS-B"

$loglikelihood
[1] 224.6033

$phiHat
numeric(0)

$thetaHat
[1] 0.6993876

$convergence
[1] 0

$algorithm
[1] "L-BFGS-B"

FitARMA documentation built on May 2, 2019, 9:33 a.m.