R help - Jul 2008 - A quick question about lm()

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!
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If I understand correctly, try:

names(summary(lm(...)))

On Mon, Jul 7, 2008 at 10:38 AM, rlearner309 <unixunix99 at gmail.com>
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!
> --
> View this message in context:
http://www.nabble.com/A-quick-question-about-lm%28%29-tp18316864p18316864.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at r-project.org mailing list
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> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>


-- 
Henrique Dallazuanna
Curitiba-Paran?-Brasil
25? 25' 40" S 49? 16' 22" O

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.

--------------------------------------------------------------------
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
------------------------------ XFMail ------------------------------

rlearner309 wrote:
> I have a simple regression using lm().
model <- lm(dist ~ speed, data = cars)
sModel <- summary(model)
> 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,
It is recommended to extract the information using coef() or resid() as in

coef(model)  # or coefficients(model)
resid(model) # or residuals(model)
> 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?
str(sModel)

sModel$r.squared
sModel$adj.r.squared

HTH,
Tobias