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Subject: Re: [R] Using PCA to filter a series
I suppose I could calculate the eigenvectors directly and not worry about
centering the time-series, since they essentially the same range to begin
with:
vec - eigen(cor(cbind(d1,d2,d3,d4)))$vector
cp - cbind(d1,d2,d3,d4)%*%vec
cp1 - cp
-
From: Jonathan Thayn [mailto:jth...@ilstu.edu]
Sent: Thursday, October 2, 2014 11:11 PM
To: David L Carlson
Cc: r-help@r-project.org
Subject: Re: [R] Using PCA to filter a series
I suppose I could calculate the eigenvectors directly and not worry about
centering the time-series, since
I have four time-series of similar data. I would like to combine these into a
single, clean time-series. I could simply find the mean of each time period,
but I think that using principal components analysis should extract the most
salient pattern and ignore some of the noise. I can compute
On Oct 2, 2014, at 12:18 PM, Jonathan Thayn jth...@ilstu.edu wrote:
I have four time-series of similar data. I would like to combine these into
a single, clean time-series. I could simply find the mean of each time
period, but I think that using principal components analysis should extract
On Oct 2, 2014, at 2:29 PM, Jonathan Thayn jth...@ilstu.edu wrote:
Hi Don. I would like to de-rotate� the first component back to its original
state so that it aligns with the original time-series. My goal is to create a
�cleaned�, or a �model� time-series from which noise has been removed.
] On
Behalf Of Don McKenzie
Sent: Thursday, October 2, 2014 4:39 PM
To: Jonathan Thayn
Cc: r-help@r-project.org
Subject: Re: [R] Using PCA to filter a series
On Oct 2, 2014, at 2:29 PM, Jonathan Thayn jth...@ilstu.edu wrote:
Hi Don. I would like to de-rotate� the first component back to its original
University
College Station, TX 77840-4352
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Don McKenzie
Sent: Thursday, October 2, 2014 4:39 PM
To: Jonathan Thayn
Cc: r-help@r-project.org
Subject: Re: [R] Using PCA to filter a series
On Oct 2, 2014
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