Hi Bert, Thank you for your message. I am looking into ave() and tapply() as you suggested but at the same time I have prepared a example of input and output files, just in case you or someone else would like to make an attempt to generate a code that goes from input to output.
Please see below or download it from https://www.dropbox.com/s/qhmpkkrejjkpbkx/sample_code.txt?dl=0 # this is (an extract of) the INPUT file I have: f1 <- structure(list(v1 = c("A", "A", "A", "A", "A", "A", "B", "B", "B", "B", "B", "B"), v2 = c("A", "B", "C", "A", "B", "C", "A", "B", "C", "A", "B", "C"), v3 = c("B", "B", "B", "C", "C", "C", "B", "B", "B", "C", "C", "C"), v4 = c(18.18530, 3.43806,0.00273, 1.42917, 1.05786, 0.00042, 2.37232, 3.01835, 0, 1.13430, 0.92872, 0)), .Names = c("v1", "v2", "v3", "v4"), class = "data.frame", row.names = c(2L, 9L, 11L, 41L, 48L, 50L, 158L, 165L, 167L, 197L, 204L, 206L)) # this is (an extract of) the OUTPUT file I would like to obtain: f2 <- structure(list(v1 = c("A", "A", "A", "A", "A", "A", "B", "B", "B", "B", "B", "B"), v2 = c("A", "B", "C", "A", "B", "C", "A", "B", "C", "A", "B", "C"), v3 = c("B", "B", "B", "C", "C", "C", "B", "B", "B", "C", "C", "C"), v4 = c(17.83529, 3.43806,0.00295, 1.77918, 1.05786, 0.0002, 2.37232, 3.01835, 0, 1.13430, 0.92872, 0)), .Names = c("v1", "v2", "v3", "v4"), class = "data.frame", row.names = c(2L, 9L, 11L, 41L, 48L, 50L, 158L, 165L, 167L, 197L, 204L, 206L)) # please notice that while the aggregated v4 on v3 has changed … aggregate(f1[,c("v4")],list(f1$v3),sum) aggregate(f2[,c("v4")],list(f2$v3),sum) # … the aggregated v4 over v1xv2 has remained unchanged: aggregate(f1[,c("v4")],list(f1$v1,f1$v2),sum) aggregate(f2[,c("v4")],list(f2$v1,f2$v2),sum) Thank you very much in advance for your assitance. Luca 2015-03-21 13:18 GMT+01:00 Bert Gunter <gunter.ber...@gene.com>: > 1. Still not sure what you mean, but maybe look at ?ave and ?tapply, > for which ave() is a wrapper. > > 2. You still need to heed the rest of Jeff's advice. > > Cheers, > Bert > > Bert Gunter > Genentech Nonclinical Biostatistics > (650) 467-7374 > > "Data is not information. Information is not knowledge. And knowledge > is certainly not wisdom." > Clifford Stoll > > > > > On Sat, Mar 21, 2015 at 4:53 AM, Luca Meyer <lucam1...@gmail.com> wrote: > > Hi Jeff & other R-experts, > > > > Thank you for your note. I have tried myself to solve the issue without > > success. > > > > Following your suggestion, I am providing a sample of the dataset I am > > using below (also downloadble in plain text from > > https://www.dropbox.com/s/qhmpkkrejjkpbkx/sample_code.txt?dl=0): > > > > #this is an extract of the overall dataset (n=1200 cases) > > f1 <- structure(list(v1 = c("A", "A", "A", "A", "A", "A", "B", "B", > > "B", "B", "B", "B"), v2 = c("A", "B", "C", "A", "B", "C", "A", > > "B", "C", "A", "B", "C"), v3 = c("B", "B", "B", "C", "C", "C", > > "B", "B", "B", "C", "C", "C"), v4 = c(18.1853007621835, 3.43806581506388, > > 0.002733567617055, 1.42917483425029, 1.05786640463504, > > 0.000420548864162308, > > 2.37232740842861, 3.01835841813241, 0, 1.13430282139936, > 0.928725667117666, > > 0)), .Names = c("v1", "v2", "v3", "v4"), class = "data.frame", row.names > = > > c(2L, > > 9L, 11L, 41L, 48L, 50L, 158L, 165L, 167L, 197L, 204L, 206L)) > > > > I need to find a automated procedure that allows me to adjust v3 > marginals > > while maintaining v1xv2 marginals unchanged. > > > > That is: modify the v4 values you can find by running: > > > > aggregate(f1[,c("v4")],list(f1$v3),sum) > > > > while maintaining costant the values you can find by running: > > > > aggregate(f1[,c("v4")],list(f1$v1,f1$v2),sum) > > > > Now does it make sense? > > > > Please notice I have tried to build some syntax that tries to modify > values > > within each v1xv2 combination by computing sum of v4, row percentage in > > terms of v4, and there is where my effort is blocked. Not really sure > how I > > should proceed. Any suggestion? > > > > Thanks, > > > > Luca > > > > > > 2015-03-19 2:38 GMT+01:00 Jeff Newmiller <jdnew...@dcn.davis.ca.us>: > > > >> I don't understand your description. The standard practice on this list > is > >> to provide a reproducible R example [1] of the kind of data you are > working > >> with (and any code you have tried) to go along with your description. In > >> this case, that would be two dputs of your input data frames and a dput > of > >> an output data frame (generated by hand from your input data frame). > >> (Probably best to not use the full number of input values just to keep > the > >> size down.) We could then make an attempt to generate code that goes > from > >> input to output. > >> > >> Of course, if you post that hard work using HTML then it will get > >> corrupted (much like the text below from your earlier emails) and we > won't > >> be able to use it. Please learn to post from your email software using > >> plain text when corresponding with this mailing list. > >> > >> [1] > >> > http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example > >> > --------------------------------------------------------------------------- > >> Jeff Newmiller The ..... ..... Go > Live... > >> DCN:<jdnew...@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. > >> > >> On March 18, 2015 9:05:37 AM PDT, Luca Meyer <lucam1...@gmail.com> > wrote: > >> >Thanks for you input Michael, > >> > > >> >The continuous variable I have measures quantities (down to the 3rd > >> >decimal level) so unfortunately are not frequencies. > >> > > >> >Any more specific suggestions on how that could be tackled? > >> > > >> >Thanks & kind regards, > >> > > >> >Luca > >> > > >> > > >> >=== > >> > > >> >Michael Friendly wrote: > >> >I'm not sure I understand completely what you want to do, but > >> >if the data were frequencies, it sounds like task for fitting a > >> >loglinear model with the model formula > >> > > >> >~ V1*V2 + V3 > >> > > >> >On 3/18/2015 2:17 AM, Luca Meyer wrote: > >> >>* Hello, > >> >*>>* I am facing a quite challenging task (at least to me) and I was > >> >wondering > >> >*>* if someone could advise how R could assist me to speed the task up. > >> >*>>* I am dealing with a dataset with 3 discrete variables and one > >> >continuous > >> >*>* variable. The discrete variables are: > >> >*>>* V1: 8 modalities > >> >*>* V2: 13 modalities > >> >*>* V3: 13 modalities > >> >*>>* The continuous variable V4 is a decimal number always greater than > >> >zero in > >> >*>* the marginals of each of the 3 variables but it is sometimes equal > >> >to zero > >> >*>* (and sometimes negative) in the joint tables. > >> >*>>* I have got 2 files: > >> >*>>* => one with distribution of all possible combinations of V1xV2 > >> >(some of > >> >*>* which are zero or neagtive) and > >> >*>* => one with the marginal distribution of V3. > >> >*>>* I am trying to build the long and narrow dataset V1xV2xV3 in such > >> >a way > >> >*>* that each V1xV2 cell does not get modified and V3 fits as closely > >> >as > >> >*>* possible to its marginal distribution. Does it make sense? > >> >*>>* To be even more specific, my 2 input files look like the > >> >following. > >> >*>>* FILE 1 > >> >*>* V1,V2,V4 > >> >*>* A, A, 24.251 > >> >*>* A, B, 1.065 > >> >*>* (...) > >> >*>* B, C, 0.294 > >> >*>* B, D, 2.731 > >> >*>* (...) > >> >*>* H, L, 0.345 > >> >*>* H, M, 0.000 > >> >*>>* FILE 2 > >> >*>* V3, V4 > >> >*>* A, 1.575 > >> >*>* B, 4.294 > >> >*>* C, 10.044 > >> >*>* (...) > >> >*>* L, 5.123 > >> >*>* M, 3.334 > >> >*>>* What I need to achieve is a file such as the following > >> >*>>* FILE 3 > >> >*>* V1, V2, V3, V4 > >> >*>* A, A, A, ??? > >> >*>* A, A, B, ??? > >> >*>* (...) > >> >*>* D, D, E, ??? > >> >*>* D, D, F, ??? > >> >*>* (...) > >> >*>* H, M, L, ??? > >> >*>* H, M, M, ??? > >> >*>>* Please notice that FILE 3 need to be such that if I aggregate on > >> >V1+V2 I > >> >*>* recover exactly FILE 1 and that if I aggregate on V3 I can recover > >> >a file > >> >*>* as close as possible to FILE 3 (ideally the same file). > >> >*>>* Can anyone suggest how I could do that with R? > >> >*>>* Thank you very much indeed for any assistance you are able to > >> >provide. > >> >*>>* Kind regards, > >> >*>>* Luca* > >> > > >> > [[alternative HTML version deleted]] > >> > > >> >______________________________________________ > >> >R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > >> >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. > >> > >> > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > > 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. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
