Hi David, hello R-experts Thank you for your input. I have tried the syntax you suggested but unfortunately the marginal distributions v1xv2 change after the manipulation. Please see below or https://www.dropbox.com/s/qhmpkkrejjkpbkx/sample_code.txt?dl=0 for the syntax.
> rm(list=ls()) > > # this is usual (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)) > > #first I order the file such that I have 6 distinct v1xv2 combinations > f1 <- f1[order(f1$v1,f1$v2),] > > # then I compute (manually) the relative importance of each v1xv2 combination: > tAA <- (18.18530+1.42917)/(18.18530+1.42917+3.43806+1.05786+0.00273+0.00042+2.37232+1.13430+3.01835+0.92872+0.00000+0.00000) # this is for combination v1=A & v2=A > tAB <- (3.43806+1.05786)/(18.18530+1.42917+3.43806+1.05786+0.00273+0.00042+2.37232+1.13430+3.01835+0.92872+0.00000+0.00000) # this is for combination v1=A & v2=B > tAC <- (0.00273+0.00042)/(18.18530+1.42917+3.43806+1.05786+0.00273+0.00042+2.37232+1.13430+3.01835+0.92872+0.00000+0.00000) # this is for combination v1=A & v2=C > tBA <- (2.37232+1.13430)/(18.18530+1.42917+3.43806+1.05786+0.00273+0.00042+2.37232+1.13430+3.01835+0.92872+0.00000+0.00000) # this is for combination v1=B & v2=A > tBB <- (3.01835+0.92872)/(18.18530+1.42917+3.43806+1.05786+0.00273+0.00042+2.37232+1.13430+3.01835+0.92872+0.00000+0.00000) # this is for combination v1=B & v2=B > tBC <- (0.00000+0.00000)/(18.18530+1.42917+3.43806+1.05786+0.00273+0.00042+2.37232+1.13430+3.01835+0.92872+0.00000+0.00000) # this is for combination v1=B & v2=C > # and just to make sure I have not made mistakes the following should be equal to 1 > tAA+tAB+tAC+tBA+tBB+tBC [1] 1 > > # procedure suggested by David Winsemius > lookarr <- array(NA, dim=c(length(unique(f1$v1)),length(unique(f1$v2)),length(unique(f1$v3)) ) , dimnames=list( unique(f1$v1), unique(f1$v2), unique(f1$v3) ) ) > lookarr[] <- c(tAA,tAA,tAB,tAB,tAC,tAC,tBA,tBA,tBB,tBB,tBC,tBC) > lookarr["A","B","C"] [1] 0.1250369 > lookarr[ with(f1, cbind(v1, v2, v3)) ] [1] 6.213554e-01 1.110842e-01 1.424236e-01 1.250369e-01 9.978703e-05 0.000000e+00 6.213554e-01 1.110842e-01 1.424236e-01 1.250369e-01 9.978703e-05 [12] 0.000000e+00 > f1$v4mod <- f1$v4*lookarr[ with(f1, cbind(v1,v2,v3)) ] > > # i compare original vs modified marginal distributions > aggregate(v4~v1*v2,f1,sum) v1 v2 v4 1 A A 19.61447 2 B A 3.50662 3 A B 4.49592 4 B B 3.94707 5 A C 0.00315 6 B C 0.00000 > aggregate(v4mod~v1*v2,f1,sum) v1 v2 v4mod 1 A A 1.145829e+01 2 B A 1.600057e+00 3 A B 6.219326e-01 4 B B 5.460087e-01 5 A C 2.724186e-07 6 B C 0.000000e+00 > aggregate(v4~v3,f1,sum) v3 v4 1 B 27.01676 2 C 4.55047 > aggregate(v4mod~v3,f1,sum) v3 v4mod 1 B 13.6931347 2 C 0.5331569 Any suggestion on how this can be fixed? Remember, I am searching for a solution where by aggregate(v4~v1*v2,f1,sum)==aggregate(v4~v1*v2,f1,sum) while aggregate(v4~v3,f1,sum)!=aggregate(v4mod~v3,f1,sum) by specified amounts (see my earlier example). Thank you very much, Luca 2015-03-22 22:11 GMT+01:00 David Winsemius <dwinsem...@comcast.net>: > > On Mar 22, 2015, at 1:12 PM, Luca Meyer wrote: > > > Hi Bert, > > > > Maybe I did not explain myself clearly enough. But let me show you with a > > manual example that indeed what I would like to do is feasible. > > > > The following is also available for download from > > https://www.dropbox.com/s/qhmpkkrejjkpbkx/sample_code.txt?dl=0 > > > > rm(list=ls()) > > > > This is usual (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 are the initial marginal distributions > > > > aggregate(v4~v1*v2,f1,sum) > > aggregate(v4~v3,f1,sum) > > > > First I order the file such that I have nicely listed 6 distinct v1xv2 > > combinations. > > > > f1 <- f1[order(f1$v1,f1$v2),] > > > > Then I compute (manually) the relative importance of each v1xv2 > combination: > > > > tAA <- > > > (18.18530+1.42917)/(18.18530+1.42917+3.43806+1.05786+0.00273+0.00042+2.37232+1.13430+3.01835+0.92872+0.00000+0.00000) > > # this is for combination v1=A & v2=A > > tAB <- > > > (3.43806+1.05786)/(18.18530+1.42917+3.43806+1.05786+0.00273+0.00042+2.37232+1.13430+3.01835+0.92872+0.00000+0.00000) > > # this is for combination v1=A & v2=B > > tAC <- > > > (0.00273+0.00042)/(18.18530+1.42917+3.43806+1.05786+0.00273+0.00042+2.37232+1.13430+3.01835+0.92872+0.00000+0.00000) > > # this is for combination v1=A & v2=C > > tBA <- > > > (2.37232+1.13430)/(18.18530+1.42917+3.43806+1.05786+0.00273+0.00042+2.37232+1.13430+3.01835+0.92872+0.00000+0.00000) > > # this is for combination v1=B & v2=A > > tBB <- > > > (3.01835+0.92872)/(18.18530+1.42917+3.43806+1.05786+0.00273+0.00042+2.37232+1.13430+3.01835+0.92872+0.00000+0.00000) > > # this is for combination v1=B & v2=B > > tBC <- > > > (0.00000+0.00000)/(18.18530+1.42917+3.43806+1.05786+0.00273+0.00042+2.37232+1.13430+3.01835+0.92872+0.00000+0.00000) > > # this is for combination v1=B & v2=C > > # and just to make sure I have not made mistakes the following should be > > equal to 1 > > tAA+tAB+tAC+tBA+tBB+tBC > > > > Next, I know I need to increase v4 any time v3=B and the total increase I > > need to have over the whole dataset is 29-27.01676=1.98324. In turn, I > need > > to dimish v4 any time V3=C by the same amount (4.55047-2.56723=1.98324). > > This aspect was perhaps not clear at first. I need to move v4 across v3 > > categories, but the totals will always remain unchanged. > > > > Since I want the data alteration to be proportional to the v1xv2 > > combinations I do the following: > > > > f1$v4 <- ifelse (f1$v1=="A" & f1$v2=="A" & f1$v3=="B", > f1$v4+(tAA*1.98324), > > f1$v4) > > f1$v4 <- ifelse (f1$v1=="A" & f1$v2=="A" & f1$v3=="C", > f1$v4-(tAA*1.98324), > > f1$v4) > > f1$v4 <- ifelse (f1$v1=="A" & f1$v2=="B" & f1$v3=="B", > f1$v4+(tAB*1.98324), > > f1$v4) > > f1$v4 <- ifelse (f1$v1=="A" & f1$v2=="B" & f1$v3=="C", > f1$v4-(tAB*1.98324), > > f1$v4) > > f1$v4 <- ifelse (f1$v1=="A" & f1$v2=="C" & f1$v3=="B", > f1$v4+(tAC*1.98324), > > f1$v4) > > f1$v4 <- ifelse (f1$v1=="A" & f1$v2=="C" & f1$v3=="C", > f1$v4-(tAC*1.98324), > > f1$v4) > > f1$v4 <- ifelse (f1$v1=="B" & f1$v2=="A" & f1$v3=="B", > f1$v4+(tBA*1.98324), > > f1$v4) > > f1$v4 <- ifelse (f1$v1=="B" & f1$v2=="A" & f1$v3=="C", > f1$v4-(tBA*1.98324), > > f1$v4) > > f1$v4 <- ifelse (f1$v1=="B" & f1$v2=="B" & f1$v3=="B", > f1$v4+(tBB*1.98324), > > f1$v4) > > f1$v4 <- ifelse (f1$v1=="B" & f1$v2=="B" & f1$v3=="C", > f1$v4-(tBB*1.98324), > > f1$v4) > > f1$v4 <- ifelse (f1$v1=="B" & f1$v2=="C" & f1$v3=="B", > f1$v4+(tBC*1.98324), > > f1$v4) > > f1$v4 <- ifelse (f1$v1=="B" & f1$v2=="C" & f1$v3=="C", > f1$v4-(tBC*1.98324), > > f1$v4) > > > > Seems that this could be done a lot more simply with a lookup matrix and > ordinary indexing > > > lookarr <- array(NA, > dim=c(length(unique(f1$v1)),length(unique(f1$v2)),length(unique(f1$v3)) ) , > dimnames=list( unique(f1$v1), unique(f1$v2), unique(f1$v3) ) ) > > lookarr[] <- c(tAA,tAA,tAB,tAB,tAC,tAC,tBA,tBA, > tBB, tBB, tBC, tBC) > > > lookarr[ "A","B","C"] > [1] 0.1250369 > > > lookarr[ with(f1, cbind(v1, v2, v3)) ] > [1] 6.213554e-01 1.110842e-01 1.424236e-01 1.250369e-01 9.978703e-05 > [6] 0.000000e+00 6.213554e-01 1.110842e-01 1.424236e-01 1.250369e-01 > [11] 9.978703e-05 0.000000e+00 > > f1$v4mod <- f1$v4*lookarr[ with(f1, cbind(v1,v2,v3)) ] > > f1 > v1 v2 v3 v4 v4mod > 2 A A B 18.18530 1.129954e+01 > 41 A A C 1.42917 1.587582e-01 > 9 A B B 3.43806 4.896610e-01 > 48 A B C 1.05786 1.322716e-01 > 11 A C B 0.00273 2.724186e-07 > 50 A C C 0.00042 0.000000e+00 > 158 B A B 2.37232 1.474054e+00 > 197 B A C 1.13430 1.260028e-01 > 165 B B B 3.01835 4.298844e-01 > 204 B B C 0.92872 1.161243e-01 > 167 B C B 0.00000 0.000000e+00 > 206 B C C 0.00000 0.000000e+00 > > -- > david. > > > > This are the final marginal distributions: > > > > aggregate(v4~v1*v2,f1,sum) > > aggregate(v4~v3,f1,sum) > > > > Can this procedure be made programmatic so that I can run it on the > > (8x13x13) categories matrix? if so, how would you do it? I have really > hard > > time to do it with some (semi)automatic procedure. > > > > Thank you very much indeed once more :) > > > > Luca > > > > > > 2015-03-22 18:32 GMT+01:00 Bert Gunter <gunter.ber...@gene.com>: > > > >> Nonsense. You are not telling us something or I have failed to > >> understand something. > >> > >> Consider: > >> > >> v1 = c("a","b") > >> v2 = "c("a","a") > >> > >> It is not possible to change the value of a sum of values > >> corresponding to v2="a" without also changing that for v1, which is > >> not supposed to change according to my understanding of your > >> specification. > >> > >> So I'm done. > >> > >> -- 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 Sun, Mar 22, 2015 at 8:28 AM, Luca Meyer <lucam1...@gmail.com> > wrote: > >>> Sorry forgot to keep the rest of the group in the loop - Luca > >>> ---------- Forwarded message ---------- > >>> From: Luca Meyer <lucam1...@gmail.com> > >>> Date: 2015-03-22 16:27 GMT+01:00 > >>> Subject: Re: [R] Joining two datasets - recursive procedure? > >>> To: Bert Gunter <gunter.ber...@gene.com> > >>> > >>> > >>> Hi Bert, > >>> > >>> That is exactly what I am trying to achieve. Please notice that > negative > >> v4 > >>> values are allowed. I have done a similar task in the past manually by > >>> recursively alterating v4 distribution across v3 categories within fix > >> each > >>> v1&v2 combination so I am quite positive it can be achieved but > honestly > >> I > >>> took me forever to do it manually and since this is likely to be an > >>> exercise I need to repeat from time to time I wish I could learn how to > >> do > >>> it programmatically.... > >>> > >>> Thanks again for any further suggestion you might have, > >>> > >>> Luca > >>> > >>> > >>> 2015-03-22 16:05 GMT+01:00 Bert Gunter <gunter.ber...@gene.com>: > >>> > >>>> Oh, wait a minute ... > >>>> > >>>> You still want the marginals for the other columns to be as > originally? > >>>> > >>>> If so, then this is impossible in general as the sum of all the values > >>>> must be what they were originally and you cannot therefore choose your > >>>> values for V3 arbitrarily. > >>>> > >>>> Or at least, that seems to be what you are trying to do. > >>>> > >>>> -- 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 Sun, Mar 22, 2015 at 7:55 AM, Bert Gunter <bgun...@gene.com> > wrote: > >>>>> I would have thought that this is straightforward given my previous > >>>> email... > >>>>> > >>>>> Just set z to what you want -- e,g, all B values to 29/number of B's, > >>>>> and all C values to 2.567/number of C's (etc. for more categories). > >>>>> > >>>>> A slick but sort of cheat way to do this programmatically -- in the > >>>>> sense that it relies on the implementation of factor() rather than > its > >>>>> API -- is: > >>>>> > >>>>> y <- f1$v3 ## to simplify the notation; could be done using with() > >>>>> z <- (c(29,2.567)/table(y))[c(y)] > >>>>> > >>>>> Then proceed to z1 as I previously described > >>>>> > >>>>> -- 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 Sun, Mar 22, 2015 at 2:00 AM, Luca Meyer <lucam1...@gmail.com> > >> wrote: > >>>>>> 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]] > > > David Winsemius > Alameda, CA, USA > > [[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.