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 Hands-On Intermediate Econometrics Using R: Templates for Extending Dozens of Practical Examples [With CDROM] by Hrishikesh D. Vinod (2008) Basically how you proceed depends a lot on what you are trying to achieve. Best Regards John On 5 August 2012 23:04, Roberto Moscetti <rmosce...@unitus.it> wrote: > 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 book (or literature) than can help me? > > Thank you very much for your time and suggestions. > > Best regards, > Roberto > > Il 05/08/2012 12:55, Jeff Newmiller ha scritto: > >> 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 each other, and >> omit the redundant ones next iteration of your analysis, using (for example) >> the approach suggested by Uwe. Deciding WHICH of the redundant inputs is >> most appropriate to keep is the part computers are not so good at... that is >> where you must be smarter or more creative than the computer. >> >> Also, it would help you get responses if you included the context (earlier >> discussion) in your replies.. most people do not use Nabble here. Reading >> and following the requests in the footer of every message will also help. >> >> --------------------------------------------------------------------------- >> Jeff Newmiller The ..... ..... Go >> Live... >> DCN:<jdnew...@dcn.davis.ca.us> Basics: ##.#. ##.#. Live >> Go... >> Live: OO#.. Dead: OO#.. Playing >> Research Engineer (Solar/Batteries O.O#. #.O#. with >> /Software/Embedded Controllers) .OO#. .OO#. >> rocks...1k >> >> --------------------------------------------------------------------------- >> Sent from my phone. Please excuse my brevity. >> >> Roberto <rmosce...@unitus.it> wrote: >> >>> 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. >>> I tried to use VIF-Regression to select variables, but rfe function >>> advise >>> me with the same warning messages again. >>> >>> What do you think about that? >>> >>> Thank you very much for your help. >>> >>> Best, >>> Roberto >>> >>> >>> >>> -- >>> View this message in context: >>> >>> http://r.789695.n4.nabble.com/Package-to-remove-collinear-variables-tp4639200p4639226.html >>> Sent from the R help mailing list archive at Nabble.com. >>> >>> ______________________________________________ >>> R-help@r-project.org mailing list >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide >>> http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >> >> > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -- John C Frain Economics Department Trinity College Dublin Dublin 2 Ireland www.tcd.ie/Economics/staff/frainj/home.html mailto:fra...@tcd.ie mailto:fra...@gmail.com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.