[Rd] lm() (PR#1059)

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 `contributors()' for more information.

Type `demo()' for some demos, `help()' for on-line help, or
`help.start()' for a HTML browser interface to help.
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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