[R] curve comparison

arun smartpink111 at yahoo.com
Tue Jul 31 05:48:13 CEST 2012


Please check this article which details the method for comparison:

Statistica Sinica 17(2007), 1115-1137
Juan Carlos Pardo-Fern ́ndez, Ingrid Van Keilegom and Wenceslao Gonz ́lez-Manteiga

Also, check some examples (http://www.stat.umn.edu/geyer/old/5601/examp/kolmogorov.html).

I am not very familiar with non-parametric tests.


From: Luis Fernando García Hernández <luysgarcia at gmail.com>
To: arun <smartpink111 at yahoo.com> 
Sent: Monday, July 30, 2012 9:00 PM
Subject: Re: [R] curve comparison

Thanks both for your answer, 

Will, do you have any reference which shows me how  how to perform this analysis? I´d like to know  to find out how to do it. In my case data is similar to compare several diversity curves, I do not know if you are familiar with them.

Related to the Kolmogrov Smirnov test, I´ll try, I did not know it allowed curve comparison.

This is a great space to share questions, so thanks both for your answer!

2012/7/30 arun <smartpink111 at yahoo.com>

>You could try some non-parametric tests for comparison such as Kolmogorov-Smirnov test (ks.test() package: truncgof)or Cramer-von Mises test (cvmts.pval() package: CvM2SL2Test).
>----- Original Message -----
>From: Luis Fernando García Hernández <luysgarcia at gmail.com>
>To: r-help at r-project.org
>Sent: Monday, July 30, 2012 1:38 AM
>Subject: [R] curve comparison
>Dear R users,
>I have seven regression lines I´d like to compare, in order to find out if
>these are significatively different. The main problem is that these are
>curves,  non normal, non homogeneous data, I´ve tried to linearize them but
>it has not worked. So I´d like to know if you know any command or source in
>R which explains how to perform this kind of comparison.
>Thanks in advance for your help!
>    [[alternative HTML version deleted]]
>R-help at r-project.org mailing list
>PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.

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