R help - Oct 2009 - easy way to find all extractor functions and the datatypes of what they return

Am I asking for too much:
for any object that a stat proc returns  ( y <- lm( y~x) , etc ) ) , is there
a super convenient function like give_all_extractors( y ) that lists all
extractor functions , the datatype returned , and a text descriptor
field ("pairwisepval" "lsmean" etc)

That would just be so convenient.

What are my options for querying an object so that I can quickly learn
the extractor functions to pull out the data and manipulate it?
Will the datatypes returned usually be named vectors and named
matrices, indiced by categorical values in the data
( "Male" "Female"  "Placebo" "DrugB" etc
)? If they are indexed by 1 ,
2 , 3 , 4 , it's easier to lose track.

thanks a bunch in advance

Robert Wilkins wrote:
> Am I asking for too much:
> for any object that a stat proc returns  ( y <- lm( y~x) , etc ) ) , is
there
> a super convenient function like give_all_extractors( y ) that lists all
> extractor functions , the datatype returned , and a text descriptor
> field ("pairwisepval" "lsmean" etc)
I think that you _are_ asing for too much. (But that's not to
say that you shouldn't consider providing code for such a
function yourself.)
> 
> That would just be so convenient.
> 
> What are my options for querying an object so that I can quickly learn
> the extractor functions to pull out the data and manipulate it?
> Will the datatypes returned usually be named vectors and named
> matrices, indiced by categorical values in the data
> ( "Male" "Female"  "Placebo"
"DrugB" etc )? If they are indexed by 1 ,
> 2 , 3 , 4 , it's easier to lose track.
The way to learn about extractor functions is to read the help
pages which you would surely do before using any function that
you haven't used previously. ?lm, for example, would point you
to coef, effects, residuals, fitted, vcov. (Be aware, however,
that not all contributed packages provide help of the same
calibre as does base R.)

The other, highly recommended, way to learn about objects in R
is the str() function. Use it often.

As to your question about named objects, R is almost obsessive
about preserving names.

  -Peter Ehlers
> 
> thanks a bunch in advance
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
> 
>

Try this (where "lm" is the class of the lm output):
> methods(class = "lm")
 [1] add1.lm*           alias.lm*          anova.lm           case.names.lm*
 [5] confint.lm*        cooks.distance.lm* deviance.lm*       dfbeta.lm*
 [9] dfbetas.lm*        drop1.lm*          dummy.coef.lm*     effects.lm*
[13] extractAIC.lm*     family.lm*         formula.lm*        hatvalues.lm
[17] influence.lm*      kappa.lm           labels.lm*         logLik.lm*
[21] model.frame.lm     model.matrix.lm    plot.lm            predict.lm
[25] print.lm           proj.lm*           residuals.lm       rstandard.lm
[29] rstudent.lm        simulate.lm*       summary.lm         variable.names.lm*
[33] vcov.lm*

   Non-visible functions are asterisked


On Sat, Oct 10, 2009 at 3:21 AM, Robert Wilkins <robstdev at gmail.com>
wrote:
> Am I asking for too much:
> for any object that a stat proc returns ?( y <- lm( y~x) , etc ) ) , is
there
> a super convenient function like give_all_extractors( y ) that lists all
> extractor functions , the datatype returned , and a text descriptor
> field ("pairwisepval" "lsmean" etc)
>
> That would just be so convenient.
>
> What are my options for querying an object so that I can quickly learn
> the extractor functions to pull out the data and manipulate it?
> Will the datatypes returned usually be named vectors and named
> matrices, indiced by categorical values in the data
> ( "Male" "Female" ?"Placebo"
"DrugB" etc )? If they are indexed by 1 ,
> 2 , 3 , 4 , it's easier to lose track.
>
> thanks a bunch in advance
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>