[R] Hope fo help - functions, fits and for cycles

[ripley@stats.ox.ac.uk]

1) add1 does this for you, more efficiently!

2) You are trying to add mydata[,expl[j]]) to a formula.  That makes no
sense in the context of the formula, and I think you need to define it
as a variable in your function and then try to add that variable.

3) update within a function is tricky because of the scope rules.  It
follows the S scope rules, AFAICS.  A much better idea is to add the
variable you want either to the data argument or to the environment of the
formula.

BTW, _ is about to be deprecated, and please do not use different
assignment operators in one piece of code.  If you must use _, put spaces
around it.  Don't make life unnecessarily hard for your readers.

On 7 Jun 2002, Marketa Pavlikova wrote:

>
> 	I need a little piece of advice concerning passing data frames
> into the functions. As I do a lot of similar fits at a time, I'd like to
> write a small function doing the fits for all relevant variables
> automatically. However, I usually get error messages of the
> following kind:
>
>   	(I present here a part of a test code).
>
> #####################################################
> # Data set:
>
> ID<-c(1,2,3,4,5)
> gender<-c(1,0,0,1,0)
> age<-c(25,40,33,50,15)
> G1<-c(0,0,1,2,0)#it corresponds to
>     some gene mutations
> G2<-c(0,1,0,1,1)#I examine the
>     effect of each of them
> G3<-c(1,1,1,1,0)#corrected for
>     "clinical" variables gender and age
> response<-c(2.1,3.5,6.1,2.0,1.5)
>
> dataset<-data.frame(ID,gender,age,G1,G2,G3,response)
> GG<-c("G1","G2","G3")
>
> #   here I construct a function that makes a basic fit,
>     then updates with each variable from GG vector.
>
> trial_function(mydata,formule,expl,distr="binomial")
> {
>       n_length(expl)
>     fit.low_glm(formule, family = distr, data = mydata,
>     na.action = na.exclude)
>
>     for (j in 1:n)
>     {
>     fit_update(fit.low,~.+ mydata[,expl[j]])
>     print(mydata[,expl[j]])
>     }
> }
>
> result<-
>     trial(mydata=dataset,formule=response~gender+age,exp
>     l=GG,distr="gaussian")
>
> #   when update is off, no error message is printed and
>     the function works all right
> #   if I untag the update, I get the following message
> ######Error in eval(expr, envir, enclos) : Object
>     "mydata" not found
> #   although it passed and foung mydata correctle
>     beforehand.
>
> #   If I break the variable passing standards and define
>     mydata beforehand by
>
> mydata<-dataset
> result<-
>     trial(mydata=dataset,formule=response~gender+age,exp
>     l=GG,distr="gaussian")
>
> #   I get
> ####Error in "[.data.frame"(mydata, , expl[j]) :
> ####Object "expl" not found
>
> ####################################################
>
> Hence, it seems to me that there is some problem in passing the
> dataset into the update function inside a for cycle. When I did the
> same thing outside the function (with the same for cycle) it worked.
> Defining the variable outside the update (inside the for cycle) didn't
> help.
>
> Is there any workaround I could use?
>
> Thank you very much for your help or connection to someone who
> could help,
>
> 				Marketa Pavlikova
> 				EuroMISE Center
>
>
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-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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