FitAR: GetFitARpMLE – R documentation

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GetFitARpMLE

Exact MLE for subset ARp Models

Description

Uses built-in function arima to fit subset ARp model, that is, the subset model is formed by constraining some coefficients to zero.

Usage

GetFitARpMLE(z, pvec)

Arguments

`z`	time series
`pvec`	lags included in AR model. If pvec = 0, white noise model assumed.

Details

Due to the optimization algorithms used by arima, this method is not very reliable. The optimization may simply fail. Example 1 shows it working but in Example 2 below it fails.

Value

a list with components:

`loglikeliihood`	the exact loglikelihood
`phiHat`	estimated AR parameters
`constantTerm`	constant term in the linear regression
`pvec`	lags of estimated AR coefficient
`res`	the least squares regression residuals
`InvertibleQ`	True, if the estimated parameters are in the AR admissible region.

Author(s)

A.I. McLeod

References

McLeod, A.I. and Zhang, Y. (2006). Partial Autocorrelation Parameterization for Subset Autoregression. Journal of Time Series Analysis, 27, 599-612.

McLeod, A.I. and Zhang, Y. (2008a). Faster ARMA Maximum Likelihood Estimation, Computational Statistics and Data Analysis 52-4, 2166-2176. DOI link: http://dx.doi.org/10.1016/j.csda.2007.07.020.

McLeod, A.I. and Zhang, Y. (2008b, Submitted). Improved Subset Autoregression: With R Package. Journal of Statistical Software.

Examples

#Example 1. MLE works
z<-log(lynx)
p<-c(1,2,4,7,10,11)
GetFitARpMLE(z, p)
#
#Example 2. MLE fails with error.
p<-c(1,2,9,12)
## Not run: GetFitARpMLE(z, p)

FitAR

Subset AR Model Fitting

v1.94

GPL (>= 2)

Authors

A.I. McLeod, Ying Zhang and Changjiang Xu

Initial release

2013-03-15