[Rd] lm() (PR#1059)
Venables, Bill (CMIS, Cleveland)
Bill.Venables@CMIS.CSIRO.AU
Fri, 17 Aug 2001 09:23:39 +1000
Where's the bug?
The adjusted R-squared is an approximately unbiased estimator of the true
R^2. Like most unbiased estimators of positive parameters it can sometimes
take on negative values. Most people will understand this, too, so I don't
see much point in artificially replacing the result by zero if its value is
negative.
Bill Venables.
-----Original Message-----
From: JDiaz-Saiz@uh.edu [mailto:JDiaz-Saiz@uh.edu]
Sent: Friday, 17 August 2001 3:31 AM
To: r-devel@stat.math.ethz.ch
Cc: R-bugs@biostat.ku.dk
Subject: [Rd] lm() (PR#1059)
Full_Name: Joaquin Diaz-Saiz
Version: 1.3.0
OS: Windows
Submission from: (NULL) (129.7.120.106)
The lm() function applied to a particular data set produces a negative value
for
the adjusted R-square. See the output below.
=======================================================
R : Copyright 2001, The R Development Core Team
Version 1.3.0 (2001-06-22)
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You are welcome to redistribute it under certain conditions.
Type `license()' or `licence()' for distribution details.
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Type `q()' to quit R.
[Previously saved workspace restored]
> w<-read.table("accres.txt")
> w
V1 V2
1 9 1
2 3 1
3 8 1
4 7 1
5 12 1
6 4 0
7 13 0
8 10 0
9 9 0
10 9 0
11 6 0
> x<-w$V1
> t<-w$V2
> x
[1] 9 3 8 7 12 4 13 10 9 9 6
> t
[1] 1 1 1 1 1 0 0 0 0 0 0
> out<-lm(x~t)
> summary(out)
Call:
lm(formula = x ~ t)
Residuals:
Min 1Q Median 3Q Max
-4.80 -1.65 0.50 1.35 4.50
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.500 1.307 6.502 0.000111 ***
t -0.700 1.939 -0.361 0.726443
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
Residual standard error: 3.202 on 9 degrees of freedom
Multiple R-Squared: 0.01427, Adjusted R-squared: -0.09525
F-statistic: 0.1303 on 1 and 9 DF, p-value: 0.7264
>
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