FGN (version 2.0-12)

earfima: Exact MLE for ARFIMA

Description

The time series is corrected for the sample mean and then exact MLE is used for the other parameters.

Usage

earfima(z, order = c(0, 0, 0), lmodel = c("FD", "FGN", "PLA", "NONE"))

Arguments

z

time series

order

(p,d,q) where p=order AR, d=regular difference, q=order MA

lmodel

type of long-memory component: FD, FGN, PLA or NONE

Value

list with components:

bHat

transformed optimal parameters

alphaHat

estimate of alpha

HHat

estimate of H

dHat

estimate of d

phiHat

estimate of phi

thetaHat

estimate of theta

wLL

optimized value of Whittle approximate log-likelihood

LL

corresponding exact log-likelihood

convergence

convergence indicator

algorithm

optimization algorithm used, 1 for L-BFGS-B, 2 for Nelder-Mead, 3 for SANN

Details

The sample mean is asymptotically efficient.

Examples

z <- rnorm(100)
earfima(z, lmodel="FGN")