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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