After fitting my time series with an ARIMA model, I want to test outliers in the residuals' series. Are there any functions in R that could do this test and furtherly test whether the outlier is additive or innovational, seasonal or just one pulse?
$\begingroup$
$\endgroup$
3
-
$\begingroup$ I dont think there is one. There is detctIO which detects Innovational Outlier in TSA package. See also posts stats.stackexchange.com/questions/62237/… and stats.stackexchange.com/questions/28003/… $\endgroup$– forecasterCommented Jan 6, 2014 at 19:28
-
$\begingroup$ Check out this question as well, specially the R code by prof. Rob Hyndman. $\endgroup$– StatCommented Jan 7, 2014 at 12:51
-
$\begingroup$ Also, commercially available packages such as SPSS, SAS, and autobox does this automatically for you. support.sas.com/documentation/cdl/en/etsug/60372/HTML/default/… autobox.com/cms/index.php/afs-university/autobox-examples/… pic.dhe.ibm.com/infocenter/spssstat/v21r0m0/… $\endgroup$– forecasterCommented Jan 8, 2014 at 2:18
Add a comment
|
1 Answer
$\begingroup$
$\endgroup$
TSA package features detectIO and detectAO, but (although you haven't stated what you're trying to do, just FYI) the arimax function will only allow you to fit a model, not forecast with it.
Robert Hyndman's code in the question linked to by Stat does not identify 'types' of outliers or possible dynamic impact.
