[R] for loop

David Winsemius dwinsemius at comcast.net
Wed Aug 5 20:12:32 CEST 2009

On Aug 5, 2009, at 1:22 PM, waltzmiester wrote:

> Jim
> Settle down, just because you can't understand my post doesn't mean  
> I didn't
> follow the guidlines.
> 1)The code is commented.
> 2)The problem in the code is succinct and therefore "minimal" even  
> though it
> cannot be self contained, the user-defined function itself is.

You could for instance have simplified the problem to simply defining  
a simple
function outside the loop and then executing it within the loop (and  
getting only the result of the last evaluation .... as would be  
expected in R.)

> 3) In order for you to be able to reproduce my code, you would need  
> to to
> install 13 packages and blend in 187 lines of patch code that I  
> would need
> to send you.

Rather than adopt an attitude, why don't you (re-?)read Jim's comments  
and thoroughly. What happens, for instance, if you wrap print() around  
the Models
call? Or perhaps assign whatever it returns to an enduring object as  
an element
of a list?

> I meant that it will model (with function Models) the first species  
> in i,
> and will not model any of the others.
> -C
> jholtman wrote:
>> What do you mean by "stop"?  Is there an error message?  What are you
>> getting as output?  I don't see you saving or printing the output  
>> from
>> "Models" (whatever that is). PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>> On Wed, Aug 5, 2009 at 11:37 AM, waltzmiester<cwalte03 at shepherd.edu>
>> wrote:
>>> I am trying to get the function "Models" to work each time there  
>>> is an
>>> instance of k. This code will stop after the first model is  
>>> complete. I
>>> need
>>> it to come back and pass the next value of c into the  
>>> "Initial.State"
>>> function. any ideas?
>>> col<-c(23:28)
>>> #Setup
>>> for(k in col){
>>> Initial.State(Response=zample[,c(k,29)],
>>> Explanatory=zample[,variable_columns],
>>> IndependentResponse=population[,c(k,29)],
>>> IndependentExplanatory=population[,variable_columns])
>>> #Modeling
>>> Models(GLM=T, GAM=T, RF=T, GBM=T, TSS=T, KeepPredIndependent=T)
>>> }

David Winsemius, MD
Heritage Laboratories
West Hartford, CT

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