Dear Antti
On 20 November 2012 10:24, Antti Simola wrote:
> I have estimated system of three linear equations with one non-linear
> restrictions with nlsystemfit.
Please read the FAQ at http://www.systemfit.org/
> I was wondering how I can calculate the
> R-squared (or some alternative coeffici
Hello everyone,
I have estimated system of three linear equations with one non-linear
restrictions with nlsystemfit. I was wondering how I can calculate the
R-squared (or some alternative coefficient of determination) for the
whole system. This is automatically given by linear systemfit but no
> From: uwe.wolf...@uni-ulm.de
> To: andy_l...@merck.com
> Date: Sat, 5 Mar 2011 17:14:12 +0100
> CC: r-help@r-project.org; gunter.ber...@gene.com
> Subject: Re: [R] Coefficient of Determination for nonlinear function
>
>
un...@r-project.org] On Behalf Of Bert Gunter
> > Sent: Friday, March 04, 2011 11:21 AM
> > To: uwe.wolf...@uni-ulm.de; r-help@r-project.org
> > Subject: Re: [R] Coefficient of Determination for nonlinear function
> >
> > The coefficient of determination, R^2, is a
Uwe Wolfram wrote:
>
>
> I did fit an equation of the form 1 = f(x1,x2,x3) using a minimization
> scheme. Now I want to compute the coefficient of determination. Normally
> I would compute it as
>
> r_square = 1- sserr/sstot with sserr = sum_i (y_i - f_i) and sstot =
> sum_i (y_i - mean(y))
>
tical measure.
>
> Andy
>
>> -Original Message-
>> From: r-help-boun...@r-project.org
>> [mailto:r-help-boun...@r-project.org] On Behalf Of Bert Gunter
>> Sent: Friday, March 04, 2011 11:21 AM
>> To: uwe.wolf...@uni-ulm.de; r-help@r-project.org
>> Sub
rom: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of Bert Gunter
> Sent: Friday, March 04, 2011 11:21 AM
> To: uwe.wolf...@uni-ulm.de; r-help@r-project.org
> Subject: Re: [R] Coefficient of Determination for nonlinear function
>
> The coefficient
The coefficient of determination, R^2, is a measure of how well your
model fits versus a "NULL" model, which is that the data are constant.
In nonlinear models, as opposed to linear models, such a null model
rarely makes sense. Therefore the coefficient of determination is
generally not meaningful
Dear Subscribers,
I did fit an equation of the form 1 = f(x1,x2,x3) using a minimization
scheme. Now I want to compute the coefficient of determination. Normally
I would compute it as
r_square = 1- sserr/sstot with sserr = sum_i (y_i - f_i) and sstot =
sum_i (y_i - mean(y))
sserr is clear to me
Dear Subscribers,
I did fit an equation of the form 1 = f(x1,x2,x3) using a minimization
scheme. Now I want to compute the coefficient of determination. Normally
I would compute it as
r_square = 1- sserr/sstot with sserr = sum_i (y_i - f_i) and sstot =
sum_i (y_i - mean(y))
sserr is clear to me
As a long time nonlinear modeller, I always compute a quantity
commonly referred to as R_squared or the coefficient of
determination. However, I agree with other commentators, including
those of several years ago, that one wants to be very careful about
interpretation. In fact, I would say "DO NOT
On 17/06/2009, at 9:03 AM, stephen sefick wrote:
look at the archives - I don't remember who gave a wonderful
explanation on this topic, but it is there.
hth
Stephen Sefick
Don't know if this is what you had in mind, but Martin Maechler's
post of 28 April 2009
http://finzi.psych.upenn.edu/R
...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Derek An
Sent: Tuesday, June 16, 2009 1:51 PM
To: r-help@r-project.org
Subject: [R] Coefficient of determination
Dear all,
Is there a instruction that can help me obtain the coefficient of
determination R^2 after doing linear/nonl
look at the archives - I don't remember who gave a wonderful
explanation on this topic, but it is there.
hth
Stephen Sefick
On Tue, Jun 16, 2009 at 4:50 PM, Derek An wrote:
> Dear all,
>
> Is there a instruction that can help me obtain the coefficient of
> determination R^2 after doing linear/non
Dear all,
Is there a instruction that can help me obtain the coefficient of
determination R^2 after doing linear/nonlinear regression using lm/nls?
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/m
Dear R-users,
I used lm() to fit a standard linear regression model to a given data
set, which led to a coefficient of determination (R^2) of about
0.96. After checking the residuals I realized that they follow an
autoregressive process (AR) of order 1 (and therefore contradicting
the i.i
om the library
without using the source?
__
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
Behalf Of Eric E Harper/USABB/ABB
Sent: Wednesday, April 09, 2008 10:47 AM
To: r-help@r-project.org
Cc: Emanuel Kolb/DECRC/ABB; Hans-Werner Borcher
Thanks in advance for your kind attention.
I am using R to fit empirical data to generalized linear models. AIC (Akaike
information criterion) is a measure of the goodness of fit returned by calls
to glm(). I would also like to calculate the coefficient of determination
R2, altho
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