[R] SAS Proc summary/means as a R function

[Frank E Harrell Jr]

What is the original intent?  The bandwidth:productivity ratio is not 
looking encouraging for this problem.

Frank

On 07/13/2010 12:38 PM, schuster wrote:
>
> Hello,
>
> are you trying to pase SAS code (or lightly modified SAS code) and run it in R?
>
> Then you are right: the hard part is parsing the code. I don't believe that's
> possible without a custom parser, and even then it's really hard to parse all
> the SAS "sub languages" right: data step, macro code and macro variables, IML,
> SAS Procedures etc.
>
>
>
> On Tuesday 13 July 2010 02:39:22 pm Roger Deangelis wrote:
>> Thanks Richard and Erik,
>>
>> I hate to buy the book and not find the solution to the following:
>>
>> proc.means<- function(....) {
>>     deparse(match.call()[-1])
>> }
>>
>> proc.means(this is a sentence)
>>
>> unexpected symbol in   "proc means(this is)
>>
>> One possible solution would be to 'peek' into the memory buffer that holds
>> the
>> function arguments.
>>
>> It is easy to replicate the 'dataset' output for many SAS procs(ie
>> transpose, freq, summary, means...)
>> I am not interested in 'report writing in R'.
>>
>> The hard part is parsing the SAS syntax, I wish R had a drop down to PERL.
>>
>> per1 on;
>>
>>     some perl code
>>
>> perl off;
>>
>> also
>>
>> sas on;
>>
>>    some SAS code
>>
>> sas off;
>>
>> The purpose of parmbuff is to turn off of Rs scanning and resolution of
>> function arguments
>> and just provide the bare text between '('  and ')' in the function call.
>>
>> This is a very powerful construct.
>>
>> A function would provide something like
>>
>> sas.on(
>>
>>
>> )
>>
>


-- 
Frank E Harrell Jr   Professor and Chairman        School of Medicine
                      Department of Biostatistics   Vanderbilt University