bestm | R Documentation |
This function is used when you have a huge number of packets where you want to identify which ones are, individually, candidates for the good prediction of a response
bestm(w2mobj, y, percentage = 50)
w2mobj |
The w2m object that contains the packets you wish to preselect |
y |
The response time series |
percentage |
The percentage of the w2m packets that you wish to select |
This function naively addresses a very common problem. The object
w2mobj contains a huge number of variables which might shed some light
on the response object y
. The problem is that the dimensionality
of w2mobj
is larger than that of the length of the series y
.
The solution here is to choose a large, but not huge, subset of the variables
that might be potentially useful in correlating with y
, discard the
rest, and return the "best" or preselected variables. Then the dimensionality
is reduced and more sophisticated methods can be used to perform better
quality modelling of the response y
on the packets in w2mobj
.
A list of class w2m with the following components:
m |
A matrix containing the select packets (as columns), reordered so that the best packets come first |
ixvec |
A vector which indexes the best packets into the original supplied matrix |
pktix |
The original wavelet packet indices corresponding to each packet |
level |
As |
nlevelsWT |
The number of resolution levels in the original wavelet packet object |
cv |
The ordered correlations |
G P Nason
makewpstRO
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