[Rd] inconsistency or bug in coef() (PR#9358)
Benilton Carvalho
bcarvalh at jhsph.edu
Mon Nov 13 05:37:47 CET 2006
it doesn't appear to be a bug for me, given that one of your
coefficients is NA due to linear dependencies on your design matrix.
i prefer to think of it as a feature :-) (show only the coefficients
for the variables that do not show linear dependencies).
x=1:5
y=c(1:3, 7, 6)
fit=lm(y~x)
coef(fit)
coef(summary(fit))
b
On Nov 12, 2006, at 11:28 PM, rmh at temple.edu wrote:
> tmp <- data.frame(x=c(1,1),
> y=c(1,2))
>
> tmp.lm <- lm(y ~ x, data=tmp)
> summary(tmp.lm)
>
> coef(summary(tmp.lm))
>
> ## I consider this to be a bug. Since summary(tmp.lm) gives
> ## two rows for the coefficients, I believe the coef() function
> ## should also give two rows.
>
>
>
>> summary(tmp.lm)
>
> Call:
> lm(formula = y ~ x, data = tmp)
>
> Residuals:
> 1 2
> -0.5 0.5
>
> Coefficients: (1 not defined because of singularities)
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 1.5 0.5 3 0.205
> x NA NA NA NA
>
> Residual standard error: 0.7071 on 1 degrees of freedom
>
>> coef(summary(tmp.lm))
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 1.5 0.5 3 0.2048328
>>
>> version
> _
> platform i386-pc-mingw32
> arch i386
> os mingw32
> system i386, mingw32
> status
> major 2
> minor 4.0
> year 2006
> month 10
> day 03
> svn rev 39566
> language R
> version.string R version 2.4.0 (2006-10-03)
>>
>
>
> ## this is a related problem
>
> tmp <- data.frame(x=c(1,2),
> y=c(1,2))
>
> tmp.lm <- lm(y ~ x, data=tmp)
> summary(tmp.lm)
>
> coef(summary(tmp.lm))
>
> ## Here the summary() give NA for the values that can't be
> ## calculated and the coef() function gives NaN. I think both
> ## functions should return the same result.
>
>
>> summary(tmp.lm)
>
> Call:
> lm(formula = y ~ x, data = tmp)
>
> Residuals:
> ALL 2 residuals are 0: no residual degrees of freedom!
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 0 NA NA NA
> x 1 NA NA NA
>
> Residual standard error: NaN on 0 degrees of freedom
> Multiple R-Squared: 1, Adjusted R-squared: NaN
> F-statistic: NaN on 1 and 0 DF, p-value: NA
>
>>
>> coef(summary(tmp.lm))
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 0 NaN NaN NaN
> x 1 NaN NaN NaN
>>
>>
>
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