[R] Singularity in a regression?
ONKELINX, Thierry
Thierry.ONKELINX at inbo.be
Thu Feb 26 16:12:11 CET 2009
It looks like your data has not enough information to estimate the
parameter for metaCl. Maybe because metaCL is identical to one of the
other variables or a constant.
HTH,
Thierry
------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be
www.inbo.be
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than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data.
~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey
-----Oorspronkelijk bericht-----
Van: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
Namens Bob Gotwals
Verzonden: donderdag 26 februari 2009 13:59
Aan: r-help at r-project.org
Onderwerp: [R] Singularity in a regression?
R friends,
In a matrix of 1s and 0s, I'm getting a singularity error. Any helpful
ideas?
lm(formula = activity ~ metaF + metaCl + metaBr + metaI + metaMe +
paraF + paraCl + paraBr + paraI + paraMe)
Residuals:
Min 1Q Median 3Q Max
-4.573e-01 -7.884e-02 3.469e-17 6.616e-02 2.427e-01
Coefficients: (1 not defined because of singularities)
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.9173 0.1129 70.135 < 2e-16 ***
metaF -0.3973 0.2339 -1.698 0.115172
metaCl NA NA NA NA
metaBr 0.3454 0.1149 3.007 0.010929 *
metaI 0.4827 0.2339 2.063 0.061404 .
metaMe 0.3654 0.1149 3.181 0.007909 **
paraF 0.7675 0.1449 5.298 0.000189 ***
paraCl 0.3400 0.1449 2.347 0.036925 *
paraBr 1.0200 0.1449 7.040 1.36e-05 ***
paraI 1.3327 0.2339 5.697 9.96e-05 ***
paraMe 1.2191 0.1573 7.751 5.19e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.2049 on 12 degrees of freedom
Multiple R-squared: 0.9257, Adjusted R-squared: 0.8699
F-statistic: 16.61 on 9 and 12 DF, p-value: 1.811e-05
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