[R] coefficient of determination on a nls regression
apjaworski@mmm.com
apjaworski at mmm.com
Wed May 1 20:52:07 CEST 2002
Antonio,
For linear regression we have the following identity
total SS = regression SS + residual SS (*)
where total SS is the sum of squares of observations around their mean,
i.e.
total SS = (n-1)*var(y)
and residual SS is given by the deviance function.
R-squared is defined as
R^2 = regression SS/ total SS = 1 - residual SS/total SS.
You can use this last formula to define a similar quantity for nonlinear
regression. You have to remember that R^2 does not have its usual meaning
for NLS. In fact, the basic identity (*) does not hold and the residuals
do not add up to zero.
Hope this helps,
Andy
__________________________________
Andy Jaworski
Engineering Systems Technology Center
3M Center, 518-1-01
St. Paul, MN 55144-1000
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E-mail: apjaworski at mmm.com
Tel: (651) 733-6092
Fax: (651) 736-3122
"Antonio
Olinto" To: "R-help" <r-help at stat.math.ethz.ch>
<aolinto at bignet cc: (bcc: Andrzej P. Jaworski/US-Corporate/3M/US)
.com.br> Subject: [R] coefficient of determination on a nls regression
05/01/2002
12:21
Hello R-users,
How can I caculate the coefficient of determination (r-squared, r2) from a
nls regression model?
r2 = regression SS / total SS
The regression SS is given by deviance(model), isn't it? And what about
total SSQ?
Thanks,
Antonio Olinto
São Paulo Fisheries Institute
Brasil
www.institutopesca.sp.gov.br
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