[R] distance from fitted line
eliza botto
eliza_botto at hotmail.com
Mon Oct 20 12:00:11 CEST 2014
Thankyou very much Joachim. Actually I already know the residual() command. I only wanted to know that is there a way to account for the fitted lines? its more of a criosity rather than a problem.
:)
Thankyou very much once again.
Eliza
To: eliza_botto at hotmail.com
Subject: Re: [R] distance from fitted line
From: Joachim.Audenaert at pcsierteelt.be
Date: Mon, 20 Oct 2014 11:11:21 +0200
Hello Eliza,
I'm quite new to R, but I use the residuals
function to calculate the distance from my data points to the fitted line
of my nls (non linear least squares model).
residuals(name of your fitted model)
I would check for a model that fits
your datapoints and then calculate the residuals of the model to your data.
Why do you fit the generalized Extreme Value distribution
to your points in stead
of a regression model?
Met vriendelijke groeten/Kind Regards,
Joachim Audenaert
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From:
eliza botto <eliza_botto at hotmail.com>
To:
"r-help at r-project.org"
<r-help at r-project.org>
Date:
19/10/2014 22:08
Subject:
[R] distance
from fitted line
Sent by:
r-help-bounces at r-project.org
Dear useRs,
I have the following dataset.
> dput(EB)
c(77.724, 76.708, 84.836, 85.09, 118.11, 65.024, 121.412, 63.5, 102.87,
81.3, 108.7, 110.7, 71.9, 42.2, 101, 151.4, 94, 112, 48, 73.4, 76.6, 62.2,
59.4, 114.3, 214.3, 110.5, 46, 84.7, 128.1, 45.2, 109.5, 102.3, 77.5, 61,
97.3, 78, 142, 88.2, 54, 91.4, 54.1, 96, 143.3, 153.7, 101.5, 95.8, 101,
131, 140, 189.4)
I fitted generalized Extreme Value distribution on it by using following
codes
library(nsRFA)
q=EB
lmom=Lmoments(q)
pr = par.GEV (lambda1=lmom["l1"], lambda2=lmom["l2"],
tau3=lmom["lca"])
RP = c(1.01,2, 10, 20, 50, 100, 200, 500)
quant = invF.GEV (1-1/RP, pr$xi, pr$alfa, pr$k)
qs = sort(q)
pp = 1:length(qs)/(length(qs)+1)
RPpp = 1/(1-pp)
plot(RP, quant, type="l", log="x",col="black",ylim=c(0,500),xlim=c(0.1,500))
points(RPpp, qs)
What I want to do now is to calculate the distance of all the points from
the "fitted line" and ultimately calculating RMSE of the data.
Is there a way of doing it?
Thankyou very much in advance
Eliza
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