Description Usage Arguments Details Value Author(s) References See Also Examples
Uses built-in function arima
to fit subset ARp model, that is,
the subset model is formed by constraining some coefficients to zero.
1 | GetFitARpMLE(z, pvec)
|
z |
time series |
pvec |
lags included in AR model. If pvec = 0, white noise model assumed. |
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.
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. |
A.I. McLeod
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.
FitAR
,
FitARz
,
GetFitARz
,
FitARp
,
RacfPlot
1 2 3 4 5 6 7 8 | #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)
|
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