Thank you very much for your help.
Really appreciated.
Best regards,
Roberto
Il 07/08/2012 12:18, John C Frain ha scritto:
For background have a look at http://en.wikipedia.org/wiki/Multicollinearity.
I have also used
Regression Diagnostics: Identifying Influential Data and Sources of
For background have a look at http://en.wikipedia.org/wiki/Multicollinearity.
I have also used
Regression Diagnostics: Identifying Influential Data and Sources of
Collinearity (Wiley Series in Probability and Statistics) by David A.
Belsley, Edwin Kuh and Roy E. Welsch
Sections 1.9 to 1.12 of
On Sat, Aug 4, 2012 at 11:27 PM, Roberto rmosce...@unitus.it wrote:
Hi,
I need to remove collinear variables to my Near-Infrared table of spectra.
What package can I use?
Something simple, because I am a novice about statistic.
There many methods of assessing multicollinearlity but to
On 05.08.2012 05:27, Roberto wrote:
Hi,
I need to remove collinear variables to my Near-Infrared table of spectra.
What package can I use?
Something simple, because I am a novice about statistic.
Remove those where
isTRUE(all.equal(cor(x, y), 1))
is TRUE?
Uwe Ligges
Thank you.
I do not know, because I tried to use rfe function (Backwards Feature
Selection, Caret Package) to select wavelengths useful for a prediction
model. Otherwise, rfe function give me back a lot of warning messages about
collinearity between variables.
So, I do not know if your script can be useful.
There is no magic bullet (package) for your problem. You must either learn
enough statistics to understand how to analyze your data, or consult with
someone who does.
FWIW collinearity is not in general amenable to automatic removal. However, you
can identify which inputs are collinear with
Hi,
thank you for your help. I know, I need to learn enough statistics to
understand how to process my data. The reason because of I write on this
forum is to ask to people a way to learn.
I am a postharvest researcher and statistic is not my main field, so I
try to do my best.
Do you know a
Hi,
I need to remove collinear variables to my Near-Infrared table of spectra.
What package can I use?
Something simple, because I am a novice about statistic.
Thank you.
Best regards,
Roberto
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