




Hi there,



My name is Renan X. Cortes, student of Statistics, from south of Brazil, and I'd
like to ask you a few questions about decomposition of time series.


 

In R, when I fit the decomposition using the "stl" function, an
object is returned when ask the summary of the fit, called STL.seasonal (%),
STL.trend (%) and STL.remainder (%). 

 

Once the decomposition is additive, I thought that this would be some kind of
decompositon of the variability of the time serie in terms of seasonal, trend
and residual unexplained. Just like a factorial analysis.

 

But, the sum os the %'s isn't one. In fact, in some cases the value of the
STL.seasonal or STL.trend exceeds 100%.


 


When I read the paper of the help of the function "STL: A
Seasonal-Trend Decomposition Procedure Based on Loess", I've seen
that the % of the components due the decomposition was constructed under
the eigenvalues of the operators matrices T and S. But It's not clear for me,
in the stl function in R
what exactly does these %'s means.   

 

What does these values means? Is there a practical interpretation for them? If
so, which is?


 


I attached a file showing the values.

 

This doubt is killing my nights of sleep.


 


 

Best regards,

Renan Xavier Cortes

Departament os Statistics

Universidade Federal do Rio Grande do Sul, Brasil


 		 	   		  
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