On 07-Jul-08 13:38:12, rlearner309 wrote:>
> I have a simple regression using lm().
> If I just want to check the coefficient, I can use summary(lm())$coef;
> if I need the standard error, I can use summary(lm())$s, if I need
> the residuals, I can use summary(lm())$res. OK. How can I get the
> R-squares and Adjusted R-squares using $...?
> Is there a function, like objects(), that can show all the references
> for values?
>
> Thanks a lot!
A useful function is str(), which displays the components of an object.
Example:
> X<-rnorm(10);Y<-rnorm(10)
> LM<-lm(Y~X)
> sumLM<-summary(LM)
> str(sumLM)
List of 11
$ call : language lm(formula = Y ~ X)
$ terms :Classes 'terms', 'formula' length 3 Y ~ X
.. ..- attr(*, "variables")= language list(Y, X)
.. ..- attr(*, "factors")= int [1:2, 1] 0 1
.. .. ..- attr(*, "dimnames")=List of 2
.. .. .. ..$ : chr [1:2] "Y" "X"
.. .. .. ..$ : chr "X"
.. ..- attr(*, "term.labels")= chr "X"
.. ..- attr(*, "order")= int 1
.. ..- attr(*, "intercept")= int 1
.. ..- attr(*, "response")= int 1
.. ..- attr(*, ".Environment")=<R_GlobalEnv>
.. ..- attr(*, "predvars")= language list(Y, X)
.. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric"
"numeric"
.. .. ..- attr(*, "names")= chr [1:2] "Y" "X"
$ residuals : Named num [1:10] 0.086 -0.345 -1.542 -0.168 -0.894 ...
..- attr(*, "names")= chr [1:10] "1" "2"
"3" "4" ...
$ coefficients : num [1:2, 1:4] 0.270 -0.289 0.387 0.321 0.699 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : chr [1:2] "(Intercept)" "X"
.. ..$ : chr [1:4] "Estimate" "Std. Error" "t
value" "Pr(>|t|)"
$ aliased : Named logi [1:2] FALSE FALSE
..- attr(*, "names")= chr [1:2] "(Intercept)"
"X"
$ sigma : num 1.06
$ df : int [1:3] 2 8 2
$ r.squared : num 0.0921
$ adj.r.squared: num -0.0213
$ fstatistic : Named num [1:3] 0.812 1.000 8.000
..- attr(*, "names")= chr [1:3] "value" "numdf"
"dendf"
$ cov.unscaled : num [1:2, 1:2] 0.1322 -0.0541 -0.0541 0.0912
..- attr(*, "dimnames")=List of 2
.. ..$ : chr [1:2] "(Intercept)" "X"
.. ..$ : chr [1:2] "(Intercept)" "X"
- attr(*, "class")= chr "summary.lm"
>From which you can see that the R-squared and Adjusted R-squared
are available as summary(LM)$r.squared and summary(LM)$adj.r.squared
Hoping this helps,
Ted.
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E-Mail: (Ted Harding) <Ted.Harding at manchester.ac.uk>
Fax-to-email: +44 (0)870 094 0861
Date: 07-Jul-08 Time: 15:28:19
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