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Working with Numbers generated from Regression Output

9 messages · Krunal Nanavati, Jean V Adams, suman kumar +2 more

Jeff Newmiller
# 
Stop posting HTML. What you see is NOT what we see.

As regards to your problems... you need to learn how to get data into and out of R, so please read the R Input/Output document supplied with R. The most foolproof way is to write the data to a CSV file and read it from there into a spreadsheet. Depending on your operating system you may be able to write into a clipboard for more convenience.

As to your goal of making predictions, with only a few more steps you can make those predictions using R. See the examples in the help for predict ( type "?predict.lm" without the quotes).
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Sent from my phone. Please excuse my brevity.
Krunal Nanavati <krunal.nanavati at cogitaas.com> wrote:

            

      
      
      
    

        

      
      
    

  
  


  


      

    

    

      
      

        


  

        

      Krunal Nanavati
    

    

      
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Hi Jeff,

Sorry for the previous email.

 I tried using write function, and used the following syntax

write(result,file="C:\\Users\\Krunal\\Desktop\\Book1.csv")

but it is giving the following error

Error in cat(list(...), file, sep, fill, labels, append) :
  argument 1 (type 'list') cannot be handled by 'cat'

Can you tell me where I am going wrong




Thanks & Regards,

Krunal Nanavati
9769-919198

-----Original Message-----
From: Jeff Newmiller [mailto:jdnewmil at dcn.davis.CA.us]
Sent: 27 July 2012 12:11
To: Krunal Nanavati; Jean V Adams
Cc: r-help at r-project.org
Subject: Re: [R] Working with Numbers generated from Regression Output

Stop posting HTML. What you see is NOT what we see.

As regards to your problems... you need to learn how to get data into and
out of R, so please read the R Input/Output document supplied with R. The
most foolproof way is to write the data to a CSV file and read it from there
into a spreadsheet. Depending on your operating system you may be able to
write into a clipboard for more convenience.

As to your goal of making predictions, with only a few more steps you can
make those predictions using R. See the examples in the help for predict (
type "?predict.lm" without the quotes).
---------------------------------------------------------------------------
Jeff Newmiller                        The     .....       .....  Go Live...
DCN:<jdnewmil at dcn.davis.ca.us>        Basics: ##.#.       ##.#.  Live Go...
                                      Live:   OO#.. Dead: OO#..  Playing
Research Engineer (Solar/Batteries            O.O#.       #.O#.  with
/Software/Embedded Controllers)               .OO#.       .OO#.  rocks...1k
---------------------------------------------------------------------------
Sent from my phone. Please excuse my brevity.

        
Krunal Nanavati <krunal.nanavati at cogitaas.com> wrote:

        

            

      
      
      
    

        

      
      
    

  
  


  


      

    

    

      
      

        


  

        

      David Winsemius
    

    

      
      #
    

  


  

      
On Jul 27, 2012, at 12:14 AM, Krunal Nanavati wrote:

        

            

      
      
      
    

        
(First off, we have no wat y=to know what result is. I'm guessing its  
an lm-object.

If that's correct, then you could try:

   write.csv( coef(result), file="C:\\Users\\Krunal\\Desktop\ 
\Book1.csv")

It is designed to write dataframes, but a simple list or vector of  
coefficients sould get written (after coercion).

I think you can also do this (in Windows)

   write.csv( coef(result), file="clipboard")  # and then paste into  
Excel

Excel doesn't really have a corresponding data structure to a named  
vector, so you won't get the names if you go the second route.

And finally, Excel has a /Data/Text to Columns facility that is useful  
for turning console output into columnar data. Choose the fixed format  
menu.

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      Krunal Nanavati
    

    

      
      #
    

  


  

      
Hi David,

Thanks for the reply.

With your first alternative, I am getting the beta values in different
cells in the excel file.

Is there a way to get all the information generated by the summary
function in different cells in a excel file, through the write function?

Also, can you please elaborate on your third option. I went into the data
tab in excel, and chose from text option, as I had pasted the console
output of regression in a text file. But by doing this I am getting all
the output in a single cell in excel.

Thanks for your time.

Thanks & Regards,

Krunal Nanavati
9769-919198


-----Original Message-----
From: David Winsemius [mailto:dwinsemius at comcast.net]
Sent: 27 July 2012 14:41
To: Krunal Nanavati
Cc: Jeff Newmiller; Jean V Adams; r-help at r-project.org
Subject: Re: [R] Working with Numbers generated from Regression Output

        
On Jul 27, 2012, at 12:14 AM, Krunal Nanavati wrote:

        

            

      
      
      
    

        
(First off, we have no wat y=to know what result is. I'm guessing its an
lm-object.

If that's correct, then you could try:

   write.csv( coef(result), file="C:\\Users\\Krunal\\Desktop\
\Book1.csv")

It is designed to write dataframes, but a simple list or vector of
coefficients sould get written (after coercion).

I think you can also do this (in Windows)

   write.csv( coef(result), file="clipboard")  # and then paste into Excel

Excel doesn't really have a corresponding data structure to a named
vector, so you won't get the names if you go the second route.

And finally, Excel has a /Data/Text to Columns facility that is useful for
turning console output into columnar data. Choose the fixed format menu.

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      David Winsemius
    

    

      
      #
    

  


  

      
On Jul 27, 2012, at 3:10 AM, Krunal Nanavati wrote:

        

            

      
      
      
    

        
The summary function returns a complex list object. You can see that  
list structure with this code:

#Using the example in help(lm)
ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2,10,20, labels=c("Ctl","Trt"))
weight <- c(ctl, trt)
lm.D90 <- lm(weight ~ group - 1) # omitting intercept

str(summary(lm.D90))

What you see at the console whaen you type summary(lm.D90) is somewhat  
different. It is the result of another function, print.summary(). It  
is not a visible function so when you type its name you get:

 > print.summary.lm
Error: object 'print.summary.lm' not found

But it has to be there and I took an educated guess that it was in the  
stats package and can see it by using the triple-colon infix function:

stats:::print.summary.lm

You could wrap 'as.character' around the summary object:

as.character( summary(lm.D90))

I'm guessing you do not really want all of that complexity and would  
probably be better served by learning the proper extractor functions  
for regression or summary.lm arguments linked from the help(lm) page  
in the "See Also" section;

?lm
?coef
?vcov
?fitted
?residuals
?terms

Notice that the extractor functions will return different objects from  
the model object than they do from the summary object:

 > coef( lm.D90)
groupCtl groupTrt
    5.032    4.661

 > coef( summary(lm.D90) )
          Estimate Std. Error  t value     Pr(>|t|)
groupCtl    5.032  0.2202177 22.85012 9.547128e-15
groupTrt    4.661  0.2202177 21.16542 3.615345e-14

            

      
      
      
    

        
As an example, copy the output of the three lines following the  
console call to "coef( summary(lm.D90) )" into an Excel spreadsheet.  
If the copied three cells should remain highlighted. Now click the  
Data menu and pick the "Text to Columns... " item and accept the  
defaults in  the which should be "fixed" in the fist dialog,  and the  
correct locations for the cell splits in the next ones.  You should  
now get the results split into cells. Sometimes you need to adjust the  
guesses that the program makes for where you want splits to occur, but  
the little fixed-import dialog is fairly handy, so you should learn  
it. But ... further such questions are off-topic for this list, and  
you should be getting you instructions on an Excel forum.

Also read:

http://rwiki.sciviews.org/doku.php?id=tips:data-io:ms_windows

(Note: I'm not a regular user of R or Excel on Windows, but I believe  
the actions on the  Excel for Mac 2011 should very similar to the  
behavior I dimly remember in the Windows version. I'm also old enough  
to remember the several years when Excel only existed on the Mac, but  
in those years I was using GLIM.)