[R] R-squared with Intercept set to 0 (zero) for linear regression in R is incorrect

William Dunlap wdunlap at tibco.com
Fri Jul 13 19:07:27 CEST 2012


You might want to look at 
   http://support.microsoft.com/kb/214230
entitled
   Incorrect output is returned when you use the Linear Regression (LINEST) function in Excel

Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com


> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
> Behalf Of William Dunlap
> Sent: Friday, July 13, 2012 10:04 AM
> To: Pamela Krone-Davis; r-help at r-project.org
> Subject: Re: [R] R-squared with Intercept set to 0 (zero) for linear regression in R is
> incorrect
> 
> What does Excel give for the following data, where the by-hand formula
> you gave is obviously wrong?
>    > x <- c(1, 2, 3)
>    > y <- c(13.1, 11.9, 11.0)
>    > M1 <- lm(y~x+0)
>    > sqerr <- (y- predict(M1)) ^ 2
>    > sqtot <- (y - mean(y)) ^ 2
>    > 1 - sum(sqerr)/sum(sqtot)
>   [1] -37.38707
> 
> Bill Dunlap
> Spotfire, TIBCO Software
> wdunlap tibco.com
> 
> 
> > -----Original Message-----
> > From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
> > Behalf Of Pamela Krone-Davis
> > Sent: Friday, July 13, 2012 9:01 AM
> > To: r-help at r-project.org
> > Subject: [R] R-squared with Intercept set to 0 (zero) for linear regression in R is
> > incorrect
> >
> > Hi,
> >
> > I have been using lm in R to do a linear regression and find the slope
> > coefficients and value for R-squared.  The R-squared value reported by R
> > (R^2 = 0.9558) is very different than the R-squared value when I use the
> > same equation in Exce (R^2 = 0.328).  I manually computed R-squared and the
> > Excel value is correct.  I show my code for the determination of R^2 in R.
> > When I do not set 0 as the intercept, the R^2 value is the same in R and
> > Excel.  In both cases the slope coefficient from R and from Excel are
> > identical.
> >
> > k is a data frame with two columns.
> >
> >     M1 = lm(k[,1]~k[,2] + 0)     ## set intercept to 0 and get different
> > R^2 values in R and Excel
> >     M2 = lm(k[,1]~k[,2])
> >     sumM1 = summary(M1)
> >     sumM2 = summary(M2)    ## get same value as Excel when intercept is not
> > set to 0
> >
> > Below is what R returns for sumM1:
> >
> > lm(formula = k[, 1] ~ k[, 2] + 0)
> >
> > Residuals:
> >       Min        1Q    Median        3Q       Max
> > -0.057199 -0.015857  0.003793  0.013737  0.056178
> >
> > Coefficients:
> >        Estimate Std. Error t value Pr(>|t|)
> > k[, 2]  1.05022    0.04266   24.62   <2e-16 ***
> > ---
> > Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >
> > Residual standard error: 0.02411 on 28 degrees of freedom
> > Multiple R-squared: 0.9558,     Adjusted R-squared: 0.9543
> > F-statistic: 606.2 on 1 and 28 DF,  p-value: < 2.2e-16
> >
> > Way manual determination was performed.  The value returned coincides with
> > the value from Excel:
> >
> > #### trying to figure out why the R^2 for R and Excel are so different.
> >      sqerr = (k[,1] - predict(M1))^2
> >      sqtot = (k[,1] - mean(k[,1])   ^2
> >
> >      R2 = 1 -  sum(sqerr)/sum(sqtot)     ## for 1D get 0.328   same as
> > excel value
> >
> > I am very puzzled by this.  How does R compute the value for R^2 in this
> > case? Did i write the lm incorrectly?
> >
> > Thanks
> > Pam
> >
> > PS  In case you are interested, the data I am using for hte two columns is
> > below.
> >
> > k[, 1]
> > 1]
> >  [1] 0.17170228 0.10881539 0.11843669 0.11619201 0.08441067 0.09424441
> > 0.04782264 0.09526496 0.11596476 0.10323453 0.06487894 0.08916484
> > 0.06358752 0.07945473
> > [15] 0.11213532 0.06531185 0.11503484 0.13679548 0.13762677 0.13126827
> > 0.12350649 0.12842441 0.13075654 0.15026602 0.14536351 0.07841638
> > 0.08419016 0.11995240
> > [29] 0.14425678
> >
> > > k[,2]
> >  [1] 0.11 0.10 0.11 0.10 0.10 0.09 0.10 0.09 0.09 0.11 0.09 0.10 0.09 0.10
> > 0.09 0.10 0.10 0.10 0.11 0.10 0.11 0.11 0.12 0.13 0.15 0.10 0.09 0.11 0.12
> >
> >
> > --
> > Pam Krone-Davis
> > Project Research Assistant and Grant Manager
> > PO Box 22122
> > Carmel, CA 93922
> > (831)582-3684 (o)
> > (831)324-0391 (h)
> >
> > 	[[alternative HTML version deleted]]
> 
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