[R] Automatic formula creation

[Alex van der Spek]

Thanks much to both Peter and Rui,

I am afraid that after 5 years with R I am still not able to understand 
your method Peter. Will stick with Rui's method for now...

Alex
On 08/09/2013 04:00 PM, peter dalgaard wrote:
> On Aug 9, 2013, at 13:26 , Rui Barradas wrote:
>
>> Hello,
>>
>> Maybe the following gives you some idea on how to vary the terms.
>>
>> idx <- 1:5  # or any other indexes
>> ftext <- paste(terms[idx], collapse = ' * ')
>
> You're not the first to use this sort of technique - it is happening in various parts of R's own internals too, but handling R expressions via their textual representation is really not a good principle (see fortune("rethink")) and it _does_ give rise to problems.
>
> I much prefer techniques like this:
>
>> nm <- lapply(letters[1:6], as.name)
>> Reduce(function(a,b) bquote(.(a)*.(b)), nm)
> a * b * c * d * e * f
>
>
> Similarly, use
>
>> trm <- Reduce(function(a,b) bquote(.(a)*.(b)), nm)
>> formula(bquote(I(1 - Pass149) ~  .(trm) - 1))
> I(1 - Pass149) ~ a * b * c * d * e * f - 1
>
>
>>
>> Hope this helps,
>>
>> Rui Barradas
>>
>>
>> Em 09-08-2013 11:40, Alex van der Spek escreveu:
>>> Say I want to compare all 5 term models from a choice of 28 different
>>> predictors and one known. All possible combinations of 5 out of 28 is
>>> easy to form by combn(). With some string manipulation it is also easy
>>> to make a text representation of a formula which is easy to convert by
>>> as.formula() for use in lm().
>>>
>>> The primitive part however is pasting together the terms which I do
>>> explicitly for 5 terms, like so:
>>>
>>>
>>>      ftext <- paste(terms[1], terms[2], terms[3], terms[4], terms[5],
>>> sep = ' * ')
>>>
>>>
>>> Works but is not great as I now need to edit this formula when the
>>> number of terms changes. There ought to be a better way but I can't find
>>> it.
>>>
>>> Any help much appreciated! The full block of relevant code follows:
>>> Alex van der Spek
>>>
>>> +++++++++++++++++++++++++++++++++++++++++++++++++++++++++
>>>
>>>
>>> #Try all 3 band models
>>> nbands <- 5
>>> freqs <- c('4', '5', '6_3', '8', '10', '12_7', '16', '20', '25', '32',
>>> '40', '51', '64', '81', '102', '128',
>>>             '161', '203', '256', '323', '406', '512', '645', '813',
>>> '1024', '1290', '1625', '2048')
>>> bands <- paste(rep('kHz', 28), freqs, rep('_ave', 28), sep = '')
>>> nc <- choose(28, nbands)
>>> combs <- t(combn(bands, nbands))
>>>
>>> models <- vector("list", nc)
>>> for (ic in 1:nc) {
>>>      terms <- c()
>>>      for (jc in 1:nbands) {
>>>          t <- paste('log10(', combs[ic, jc], ')', sep = '')
>>>          terms <- append(terms, t)
>>>      }
>>>
>>>      ftext <- paste(terms[1], terms[2], terms[3], terms[4], terms[5],
>>> sep = ' * ')
>>>
>>>      ftext <- paste('I(1 - Pass149) ~ ', ftext, ' - 1', sep = '')
>>>      forml <- as.formula(ftext)
>>>
>>>      plus100.lm <- lm(forml, data = sd, subset = Use == 'Cal')
>>>      plus100.sm <- step(plus100.lm, trace = 0)
>>> }
>>>
>>> ______________________________________________
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>>> PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>> ______________________________________________
>> 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.