[R] Outlier Detection for timeseries

[Pele]

Hi Hans - I tried your suggestion and it worked out well... Many thanks!!

Also, thank to everyone else for their suggestions.



Hans W. Borchers-4 wrote:
> 
> Pele <drdionc <at> yahoo.com> writes:
> 
>> 
>> 
>> Hello R users,
>> 
>> Can someone tell if there is a package in R that can do outlier detection
>> that give outputs simiilar to what I got from SAS  below.
>> 
>> Many thanks in advance for any help!
> 
> 
> I guess you are talking about the OUTLIER procedure in SAS that attempts
> to detect 'additive outliers' and 'level shifts' in a 'response' series,
> the second following Jong & Penzer's "Diagnosing shocks in time series".
> 
> I have not come across this method in R, but you might have a look into
> the
> 'robfilter' (Robust Time Series Filters) package with functions like
> 'dw.filter', 'adore.filter', or 'wrm.filter', see for instance
> 
>     "dw.filter is suitable for extracting low frequency components (the
>     signal) from a time series which may be contaminated with outliers
>     and can contain level shifts. For this, moving window techniques are 
>     applied." 
> 
> If your time series is actually a response, you might prefer to look at
> the series of residuals instead.
> 
> 
>>                               Outlier Details
>> 
>> Approx
>> Chi-    
>> Prob>
>>            Obs    Time ID         Type       Estimate      Square    
>> ChiSq
>> 
>>             12       12.000000    Additive   2792544.6      186.13   
>> <.0001
>>             13       13.000000    Additive   954302.1       21.23   
>> <.0001
>>             15       15.000000    Shift      63539.3       
>> 9.06    0.0026
>>
> 
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> 

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