[R] help with package "simsalabim"

[mauede at alice.it]

I have attached a text file representing the centralized amplitude of a signal,  sampled at 30Hz, whose length N = 6922
My goal is to remove the trend. I am using package "simsalabim".

I ran command decompSSA  with  L = length(Amps)/5
The reason is that I have SSA/MTM toolkit running in Mac/OS.  SSA/MTM documentation, relative to SSA, recommends that  N/10 <= L <= N/5. Documentation of simsalabim package recommens that L=N/2

I ran the command getSignal and felt uncomfortable at picking values for parameters C0 and r0.
I would appreciate some suggestion/guidelines because these values seem to influence the trend extraction.
I chose  C0=0.0005, r0=0.0005  which are both below the Nyquist frequency 1/Amps.dc$L = 0.0007223346

As a consequence, getSignal finds two Eigenvectors capturing the trend.
>From my experience with toolkit SSA/MTM I know this output can be misleading.
I am trying to figure out whether trend has really been found by double-checking the print-out data:

> Amps.signal$trend
    k  smoothness explainedVariance
1   1    0.134495414         26.254096
11 12  0.006693601          1.627475

The above print-out marks EOF_1 and EOF_12 as capturing all the trend in the signal.
I canNOT understand the difference between "smoothness" and  "explainedVariance"
I tried to compare such values with the leading frequency associated with EOF_1 and EOF_12.
Unluckily, I am unable to draw any comclusion:

> Amps.dc$freq[1]     #EOF_1 LEADING FREQUENCY
[1] 0.0007225434

> Amps.dc$freq[12]   #EOF_12 LEADING FREQUENCY
[1] 0.002890173

"getSignal" on-line documentation states about Trend "smoothness":
    The proportion of variance explained by the frequencies <=q omega0. 
But nowhere I could find what "q" is equal to. I guess the above sentence indicates a fraction of the nyquist frequency Omega_0 ????

"getSignal" on-line documentation states about Trend "explainedVariance":
    Percentage of the variance explained by the Eigenvalues with  rank k
Does the above variance refer to the signal variance ????

I would greatly appreciate your help at using this package properly.
Thank you in advance.
Maura 




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