Hi Bert, hello R-experts,
I am close to a solution but I still need one hint w.r.t. the following
procedure (available also from
https://www.dropbox.com/s/qhmpkkrejjkpbkx/sample_code.txt?dl=0)
rm(list=ls())
# 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 the procedure that Bert suggested (slightly adjusted):
z <- rnorm(nrow(f1)) ## or anything you want
z1 <- round(with(f1,v4 + z -ave(z,v1,v2,FUN=mean)), digits=5)
aggregate(v4~v1*v2,f1,sum)
aggregate(z1~v1*v2,f1,sum)
aggregate(v4~v3,f1,sum)
aggregate(z1~v3,f1,sum)
My question to you is: how can I set z so that I can obtain specific values
for z1-v4 in the v3 aggregation?
In other words, how can I configure the procedure so that e.g. B=29 and
C=2.56723 after running the procedure:
aggregate(z1~v3,f1,sum)
Thank you,
Luca
PS: to avoid any doubts you might have about who I am the following is my
web page: http://lucameyer.wordpress.com/
2015-03-21 18:13 GMT+01:00 Bert Gunter <gunter.ber...@gene.com>:
> ... or cleaner:
>
> z1 <- with(f1,v4 + z -ave(z,v1,v2,FUN=mean))
>
>
> Just for curiosity, was this homework? (in which case I should
> probably have not provided you an answer -- that is, assuming that I
> HAVE provided an answer).
>
> 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 7:53 AM, Bert Gunter <bgun...@gene.com> wrote:
> > z <- rnorm(nrow(f1)) ## or anything you want
> > z1 <- f1$v4 + z - with(f1,ave(z,v1,v2,FUN=mean))
> >
> >
> > aggregate(v4~v1,f1,sum)
> > aggregate(z1~v1,f1,sum)
> > aggregate(v4~v2,f1,sum)
> > aggregate(z1~v2,f1,sum)
> > aggregate(v4~v3,f1,sum)
> > aggregate(z1~v3,f1,sum)
> >
> >
> > 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 6:49 AM, Luca Meyer <lucam1...@gmail.com> wrote:
> >> 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.
> >>
> >>
>
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