est.arma.wge {tswge}

Function to calculate ML estimates of parameters of stationary ARMA models

Description

This function calculates ML estimates, computes residuals (using backcasting), estimates white noise variance for a stationary ARMA model

Usage

est.arma.wge(x, p = 0, q = 0, factor = TRUE)

Arguments

x

The realization.

p

The autoregressive order

q

the moving average order

factor

Logical variable. factor=TRUE (default) plots a factor table for estimated AR-part of model

Details

This function uses arima from base SAS and is written similarly to itsmr function arma

Value

phi

ML estimates of autoregressive parameters

theta

ML estimates of moving average parameters

res

Residuals (calculated using backcasting)

avar

Estimate of white noise variance based on backcast residuals

se.phi

Standard errors of the AR parameter estimates

se.theta

Standard errors of the MA parameter estimates

aic

AIC for estimated model

aicc

AICC for estimated model

bic

BIC for estimated model

Note

Requires CRAN package 'itsmr'. The program is based on arima from base R and arma from 'itsmr'

Author(s)

Wayne Woodward

References

"Applied Time Series Analysis with R, 2nd edition" by Woodward, Gray, and Elliott

Examples

data(fig6.2nf)
          est.arma.wge(fig6.2nf,p=2,q=1)