[R] cumulative sum by group and under some criteria

arun smartpink111 at yahoo.com
Mon Feb 25 08:20:50 CET 2013


Hello,
 head(d,2)
#  m1 n1 x1 y1 Fmm  Fnn Qm   Qn  term1_p0 term1_p1
#1  2  2  0  0   0 0.00  1 1.00 0.8145062   0.4096
#2  2  2  0  1   0 0.64  1 0.36 0.0857375   0.2048


Assuming that `x` and `y` are 'x1` and `y1`, where is 'c11` in the dataset?
res2<-do.call(rbind,lapply(lst1[lapply(lst1,nrow)!=0],function(x){
 x[,11:14]<-NA;
 x[,11:12][x$Qm<=c11,]<-cumsum(x[,9:10][x$Qm<=c11,]); 
 x[,13:14][x$Qn<=c12,]<-cumsum(x[,9:10][x$Qn<=c12,]); 
 colnames(x)[11:14]<-
 c("cterm1_P0L","cterm1_P1L","cterm1_P0H","cterm1_P1H");
 x1<-na.locf(x);
 x1[,11:14][is.na(x1[,11:14])]<-0;
 x1}))
Error in `[.data.frame`(x[, 9:10], x$Qm <= c11, ) : 
  object 'c11' not found


A.K.




----- Original Message -----
From: Zjoanna <Zjoanna2013 at gmail.com>
To: r-help at R-project.org
Cc: 
Sent: Sunday, February 24, 2013 4:48 PM
Subject: Re: [R] cumulative sum by group and under some criteria

Thanks! Solved. I have another question.

This is your code for calculated the cumulative sum. how to modify the code
if I want to add another criterion for calculating the cumulative sum:
x[,11:12][x$Qm<=c11,]<-cumsum(x[,9:10][x$Qm<=c11,]);   # cumsum if
x$Qm<=c11 & x>2
x[,13:14][x$Qn<=c12,]<-cumsum(x[,9:10][x$Qn<=c12,]);    #cumsum if x$Qn<=12
& y>2


d <- structure(list(m1 = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3),
    n1 = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3,
    3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2), x1 = c(0,
    0, 0, 1, 1, 1, 2, 2, 2, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2,
    2, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3), y1 = c(0, 1, 2, 0,
    1, 2, 0, 1, 2, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1,
    2, 0, 1, 2, 0, 1, 2, 0, 1, 2), Fmm = c(0, 0, 0, 0.7, 0.59,
    0.64, 1, 1, 1, 0, 0, 0, 0, 0.63, 0.7, 0.74, 0.68, 1, 1, 1,
    1, 0, 0, 0, 0.62, 0.63, 0.6, 0.63, 0.6, 0.68, 1, 1, 1), Fnn = c(0,
    0.64, 1, 0, 0.51, 1, 0, 0.67, 1, 0, 0.62, 0.69, 1, 0, 0.54,
    0.62, 1, 0, 0.63, 0.73, 1, 0, 0.63, 1, 0, 0.7, 1, 0, 0.7,
    1, 0, 0.58, 1), Qm = c(1, 1, 1, 0.65, 0.45, 0.36, 0.5, 0.165,
    0, 1, 1, 1, 1, 0.685, 0.38, 0.32, 0.32, 0.5, 0.185, 0.135,
    0, 1, 1, 1, 0.69, 0.37, 0.4, 0.685, 0.4, 0.32, 0.5, 0.21,
    0), Qn = c(1, 0.36, 0, 0.65, 0.45, 0, 0.5, 0.165, 0, 1, 0.38,
    0.31, 0, 0.685, 0.38, 0.32, 0, 0.5, 0.185, 0.135, 0, 1, 0.37,
    0, 0.69, 0.3, 0, 0.685, 0.3, 0, 0.5, 0.21, 0), term1_p0 =
c(0.81450625,
    0.0857375, 0.00225625, 0.0857375, 0.009025, 0.0002375, 0.00225625,
    0.0002375, 6.25e-06, 0.7737809375, 0.1221759375, 0.00643031249999999,
    0.0001128125, 0.081450625, 0.012860625, 0.000676875, 1.1875e-05,
    0.0021434375, 0.0003384375, 1.78125e-05, 3.125e-07, 0.7737809375,
    0.081450625, 0.0021434375, 0.1221759375, 0.012860625, 0.0003384375,
    0.00643031249999999, 0.000676875, 1.78125e-05, 0.0001128125,
    1.1875e-05, 3.125e-07), term1_p1 = c(0.4096, 0.2048, 0.0256,
    0.2048, 0.1024, 0.0128, 0.0256, 0.0128, 0.0016, 0.32768,
    0.24576, 0.06144, 0.00512, 0.16384, 0.12288, 0.03072, 0.00256,
    0.02048, 0.01536, 0.00384, 0.00032, 0.32768, 0.16384, 0.02048,
    0.24576, 0.12288, 0.01536, 0.06144, 0.03072, 0.00384, 0.00512,
    0.00256, 0.00032)), .Names = c("m1", "n1", "x1", "y1", "Fmm",
"Fnn", "Qm", "Qn", "term1_p0", "term1_p1"), row.names = c(NA,
33L), class = "data.frame")

library(zoo)
lst1<- split(d,list(d$m1,d$n1))
res2<-do.call(rbind,lapply(lst1[lapply(lst1,nrow)!=0],function(x){
x[,11:14]<-NA;
x[,11:12][x$Qm<=c11,]<-cumsum(x[,9:10][x$Qm<=c11,]);   # cumsum if
x$Qm<=c11 & x>2
x[,13:14][x$Qn<=c12,]<-cumsum(x[,9:10][x$Qn<=c12,]);    #cumsum if x$Qn<=12
& y>2
colnames(x)[11:14]<-
c("cterm1_P0L","cterm1_P1L","cterm1_P0H","cterm1_P1H");
x1<-na.locf(x);
x1[,11:14][is.na(x1[,11:14])]<-0;
x1}))
row.names(res2)<- 1:nrow(res2)
res2


On Sat, Feb 23, 2013 at 10:56 PM, arun kirshna [via R] <
ml-node+s789695n4659515h76 at n4.nabble.com> wrote:

> Hi,
> You can also use ?rowMins() or ?rowMaxs() from library(matrixStats)
>
>
> library(plyr)
> res2<- join(res1,d3,by=c("m1","n1"),type="inner")
>
> p0L<-0.05
> p0H<-0.05
> p1L<-0.20
> p1H<-0.20
>
> res2<- within(res2,{p1<- x/m; p2<- y/n;term2_p0<-dbinom(x1,m1, p0L,
> log=FALSE)* dbinom(y1,n1,p0H, log=FALSE)*dbinom(x-x1,m-m1, p0L, log=FALSE)*
> dbinom(y-y1,n-n1,p0H, log=FALSE);term2_p1<- dbinom(x1,m1, p1L, log=FALSE)*
> dbinom(y1,n1,p1H, log=FALSE)*dbinom(x-x1,m-m1, p1L, log=FALSE)*
> dbinom(y-y1,n-n1,p1H, log=FALSE)})
>
> Pm2<-rbeta(1000, 0.2+res2$x, 0.8+res2$m-res2$x)
> Pn2<-rbeta(1000, 0.2+res2$y, 0.8+res2$n-res2$y)
> Fm2<- ecdf(Pm2)
> Fn2<- ecdf(Pn2)
> library(matrixStats)
>  res3<- within(res2,{Fmm2<-Fm2(p1);Fnn2<- Fn2(p2);R2<-
> (Fmm2+Fnn2)/2;Fmm_f2<-rowMins(cbind(R2,Fmm2));Fnn_f2<-rowMaxs(cbind(R2,Fnn2));Qm2<-
> 1-Fmm_f2;Qn2<- 1-Fnn_f2})
> head(res3)
> #  m1 n1 x1 y1 m n x y cterm1_P0L cterm1_P1L cterm1_P0H cterm1_P1H
> term2_p1
> #1  2  2  0  0 4 4 0 0     0.9025       0.64     0.9025       0.64
> 0.16777216
> #2  2  2  0  0 4 4 0 1     0.9025       0.64     0.9025       0.64
> 0.08388608
> #3  2  2  0  0 4 4 0 2     0.9025       0.64     0.9025       0.64
> 0.01048576
> #4  2  2  0  0 4 4 1 0     0.9025       0.64     0.9025       0.64
> 0.08388608
> #5  2  2  0  0 4 4 1 1     0.9025       0.64     0.9025       0.64
> 0.04194304
> #6  2  2  0  0 4 4 1 2     0.9025       0.64     0.9025       0.64
> 0.00524288
> #      term2_p0   p2   p1   Qn2 Qm2 Fnn_f2 Fmm_f2     R2  Fnn2 Fmm2
> #1 0.6634204313 0.00 0.00 1.000 1.0  0.000    0.0 0.0000 0.000  0.0
> #2 0.0698337296 0.25 0.00 0.593 1.0  0.407    0.0 0.2035 0.407  0.0
> #3 0.0018377297 0.50 0.00 0.302 1.0  0.698    0.0 0.3490 0.698  0.0
> #4 0.0698337296 0.00 0.25 0.800 0.8  0.200    0.2 0.2000 0.000  0.4
> #5 0.0073509189 0.25 0.25 0.593 0.6  0.407    0.4 0.4035 0.407  0.4
> # 0.0001934452 0.50 0.25 0.302 0.6  0.698    0.4 0.5490 0.698  0.4
>
>
>
>
>
>
> ________________________________
> From: Joanna Zhang <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=0>>
>
> To: arun <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=1>>
>
> Sent: Saturday, February 23, 2013 5:35 PM
> Subject: Re: [R] cumulative sum by group and under some criteria
>
>
> the row wise min or max of R2, Rmm2 , for example, for the first row,
> suppose R2 = 0.63 and Fmm2 = 0.56, then Fmm_f2 = 0.63.
>
> means draw 1000 samples for each row from a beta distribution.
>
>
> On Sat, Feb 23, 2013 at 3:49 PM, arun <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=2>>
> wrote:
>
> Hi,
>
> >
> >I have a doubt:
> >When you say that min(R2,Fmm2) or max(R2,Fnn2), do you mean the
> corresponding row wise min or max. for these two columns or the maximum
> from the entire two columns.
> >
> >Also, why do you need rbeta(1000,...), should it be rbeta(240,..) because
> if you use the former the nrow from res2 is around 240 and in the formula,
> you are also using x, m , from res2, which makes no sense to me.
> >Arun
> >
> >
> >
> >
> >
> >
> >
> >
> >________________________________
> >From: Joanna Zhang <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=3>>
>
> >To: arun <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=4>>
>
> >Sent: Saturday, February 23, 2013 4:12 PM
> >
> >Subject: Re: [R] cumulative sum by group and under some criteria
> >
> >
> >sorry, these are
> >p0L<-0.05
> >p0H<-0.05
> >p1L<-0.20
> >p1H<-0.20
> >
> >
> >
> >On Sat, Feb 23, 2013 at 2:48 PM, arun <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=5>>
> wrote:
> >
> >Hi,
> >>
> >>If you give only half the information, it will be difficult to solve.
> >>
> >>
> >>d3<-structure(list(m1 = c(2, 3, 2), n1 = c(2, 2, 3), cterm1_P0L =
> c(0.9025,
> >>0.857375, 0.9025), cterm1_P1L = c(0.64, 0.512, 0.64), cterm1_P0H =
> c(0.9025,
> >>0.9025, 0.857375), cterm1_P1H = c(0.64, 0.64, 0.512)), .Names = c("m1",
> >>"n1", "cterm1_P0L", "cterm1_P1L", "cterm1_P0H", "cterm1_P1H"), row.names
> = c(NA,
> >>3L), class = "data.frame")
> >>d2<- data.frame()
> >>
> >>for (m1 in 2:3) {
> >>    for (n1 in 2:3) {
> >>        for (x1 in 0:(m1-1)) {
> >>            for (y1 in 0:(n1-1)) {
> >>        for (m in (m1+2): (7-n1)){
> >>               for (n in (n1+2):(9-m)){
> >>
> >>               for (x in x1:(x1+m-m1)){
> >>
> >>             for(y in y1:(y1+n-n1)){
> >> d2<- rbind(d2,c(m1,n1,x1,y1,m,n,x,y))
> >> }}}}}}}}
> >>colnames(d2)<-c("m1","n1","x1","y1","m","n","x","y")
> >>
> >>
> >>
> >>res1<-do.call(rbind,lapply(unique(d3$m1),function(m1)
> >> do.call(rbind,lapply(unique(d3$n1),function(n1)
> >> do.call(rbind,lapply(0:(m1-1),function(x1)
> >> do.call(rbind,lapply(0:(n1-1),function(y1)
> >> do.call(rbind,lapply((m1+2):(7-n1),function(m)
> >> do.call(rbind,lapply((n1+2):(9-m),function(n)
> >> do.call(rbind,lapply(x1:(x1+m-m1), function(x)
> >> do.call(rbind,lapply(y1:(y1+n-n1), function(y)
> >> expand.grid(m1,n1,x1,y1,m,n,x,y)) )))))))))))))))
> >> names(res1)<- c("m1","n1","x1","y1","m","n","x","y")
> >> attr(res1,"out.attrs")<-NULL
> >>res1[]<- sapply(res1,as.integer)
> >>
> >> identical(d2,res1)
> >>#[1] TRUE
> >>
> >>library(plyr)
> >>res2<- join(res1,d3,by=c("m1","n1"),type="inner")
> >>res2$p1<- x/m
> >> res2$p2<- y/n
> >>
> >>
> >>
> >>dbinom(x1,m1, p0L, log=FALSE)* dbinom(y1,n1,p0H,
> log=FALSE)*dbinom(x-x1,m-m1, p0L, log=FALSE)* dbinom(y-y1,n-n1,p0H,
> log=FALSE)
> >>#Error in dbinom(x1, m1, p0L, log = FALSE) : object 'p0L' not found
> >>A.K.
> >>
> >>
> >>
> >>________________________________
> >>
> >>From: Joanna Zhang <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=6>>
>
> >>To: arun <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=7>>
>
> >>Sent: Friday, February 22, 2013 11:02 AM
> >>
> >>Subject: Re: [R] cumulative sum by group and under some criteria
> >>
> >>
> >>Thanks!  Then I need to create new variables based on the res2.  I can't
> find Fmm_f1, Fnn_f2, R2, Qm2, Qn2 until  running the code several times and
> the values of Fnn_f2, Fmm_f2 are correct.
> >>
> >>attach(res2)
> >>res2$p1<-x/m
> >>res2$p2<-y/n
> >>res2$term2_p0 <- dbinom(x1,m1, p0L, log=FALSE)* dbinom(y1,n1,p0H,
> log=FALSE)*dbinom(x-x1,m-m1, p0L, log=FALSE)* dbinom(y-y1,n-n1,p0H,
> log=FALSE)
> >>res2$term2_p1 <- dbinom(x1,m1, p1L, log=FALSE)* dbinom(y1,n1,p1H,
> log=FALSE)*dbinom(x-x1,m-m1, p1L, log=FALSE)* dbinom(y-y1,n-n1,p1H,
> log=FALSE)
> >>Pm2<-rbeta(1000, 0.2+x, 0.8+m-x)
> >>Fm2<-ecdf(Pm2)
> >>res2$Fmm2<-Fm2(x/m)  #not correct, it comes out after running code two
> times
> >>Pn2<-rbeta(1000, 0.2+y, 0.8+n-y)
> >>Fn2<-ecdf(Pn2)
> >>res2$Fnn2<-Fn2(y/n)
> >>res2$R2<-(Fmm2+Fnn2)/2
> >>res2$Fmm_f2<-min(R2,Fmm2)  # not correct
> >>res2$Fnn_f2<-max(R2,Fnn2)
> >>res2$Qm2<-(1-Fmm_f2)
> >>res2$Qn2<-(1-Fnn_f2)
> >>detach(res2)
> >>res2
> >>head(res2)
> >>
> >>
> >>
> >>On Tue, Feb 19, 2013 at 4:09 PM, arun <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=8>>
> wrote:
> >>
>  >>Hi,
> >>>
> >>>""suppose that I have a dataset 'd'
> >>>   m1  n1    A             B     C         D
> >>>1  2  2   0.902500    0.640   0.9025    0.64
> >>>2  3  2   0.857375    0.512   0.9025    0.64
> >>>I want to add  x1 (from 0 to m1), y1(from 0 to n1), m (range from
> >>>m1+2 to 7-n1), n(from n1+2 to 9-m), x (x1 to x1+m-m1), y(y1 to
> y1+n-n1), expanding to another dataset 'd2' based on each row (combination
> of m1
> >>>and n1)""
> >>>
> >>>
> >>>Try:
> >>>
> >>>
> >>> d<-read.table(text="
> >>>
> >>>m1  n1    A             B     C         D
> >>>1  2  2   0.902500    0.640   0.9025    0.64
> >>>2  3  2   0.857375    0.512   0.9025    0.64
> >>>",sep="",header=TRUE)
> >>>
> >>>vec1<- paste(d[,1],d[,2],d[,3],d[,4],d[,5],d[,6])
> >>>res1<- do.call(rbind,lapply(vec1,function(m1)
> do.call(rbind,lapply(0:(as.numeric(substr(m1,1,1))),function(x1)
> do.call(rbind,lapply(0:(as.numeric(substr(m1,3,3))),function(y1)
> do.call(rbind,lapply((as.numeric(substr(m1,1,1))+2):(7-as.numeric(substr(m1,3,3))),function(m)
> do.call(rbind,lapply((as.numeric(substr(m1,3,3))+2):(9-m),function(n)
> >>>
> >>> do.call(rbind,lapply(x1:(x1+m-as.numeric(substr(m1,1,1))), function(x)
> >>> do.call(rbind,lapply(y1:(y1+n-as.numeric(substr(m1,3,3))), function(y)
> >>> expand.grid(m1,x1,y1,m,n,x,y)) )))))))))))))
> >>>
> >>names(res1)<- c("group","x1","y1","m","n","x","y")
> >>> res1$m1<- NA; res1$n1<- NA; res1$A<- NA; res1$B<- NA; res1$C<-
> NA;res1$D <- NA
> >>>res1[,8:13]<-do.call(rbind,lapply(strsplit(as.character(res1$group),"
> "),as.numeric))
> >>>res2<- res1[,c(8:9,2:7,10:13)]
> >>>
> >>>
> >>> head(res2)
> >>>#  m1 n1 x1 y1 m n x y      A    B      C    D
> >>>#1  2  2  0  0 4 4 0 0 0.9025 0.64 0.9025 0.64
> >>>#2  2  2  0  0 4 4 0 1 0.9025 0.64 0.9025 0.64
> >>>#3  2  2  0  0 4 4 0 2 0.9025 0.64 0.9025 0.64
> >>>#4  2  2  0  0 4 4 1 0 0.9025 0.64 0.9025 0.64
> >>>#5  2  2  0  0 4 4 1 1 0.9025 0.64 0.9025 0.64
> >>>#6  2  2  0  0 4 4 1 2 0.9025 0.64 0.9025 0.64
> >>>
> >>>
> >>>
> >>>
> >>>
> >>>
> >>>________________________________
> >>>From: Joanna Zhang <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=9>>
>
> >>>To: arun <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=10>>
>
> >>>Sent: Tuesday, February 19, 2013 11:43 AM
> >>>
> >>>Subject: Re: [R] cumulative sum by group and under some criteria
> >>>
> >>>
> >>>Thanks. I can get the data I expected (get rid of the m1=3, n1=3) using
> the join and 'inner' code, but just curious about the way to expand the
> data. There should be a way to expand the data based on each row
> (combination of the variables), unique(d3$m1 & d3$n1) ?.
> >>>
> >>>or is there a way to use 'data.frame' and 'for' loop to expand directly
> from the data? like res1<-data.frame (d3) for () {....
> >>>
> >>>
> >>>On Tue, Feb 19, 2013 at 9:55 AM, arun <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=11>>
> wrote:
> >>>
> >>>If you can provide me the output that you expect with all the rows of
> the combination in the res2, I can take a look.
> >>>>
> >>>>
> >>>>
> >>>>
> >>>>
> >>>>
> >>>>________________________________
> >>>>
> >>>>From: Joanna Zhang <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=12>>
>
> >>>>To: arun <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=13>>
>
> >>>>
>  >>>>Sent: Tuesday, February 19, 2013 10:42 AM
> >>>>
> >>>>Subject: Re: [R] cumulative sum by group and under some criteria
> >>>>
> >>>>
> >>>>Thanks. But I thougth the expanded dataset 'res1' should not have
> combination of m1=3 and n1=3 because it is based on dataset 'd3' which
> doesn't have m1=3 and n1=3, right?>
> >>>>>In the example that you provided:
> >>>>> (m1+2):(maxN-(n1+2))
> >>>>>#[1] 5
> >>>>> (n1+2):(maxN-5)
> >>>>>#[1] 4
> >>>>>#Suppose
> >>>>> x1<- 4
> >>>>> y1<- 2
> >>>>> x1:(x1+5-m1)
> >>>>>#[1] 4 5 6
> >>>>> y1:(y1+4-n1)
> >>>>>#[1] 2 3 4
> >>>>>
> >>>>> datnew<-expand.grid(5,4,4:6,2:4)
> >>>>> colnames(datnew)<- c("m","n","x","y")
> >>>>>datnew<-within(datnew,{p1<- x/m;p2<-y/n})
> >>>>>res<-cbind(datnew,d2[rep(1:nrow(d2),nrow(datnew)),])
> >>>>> row.names(res)<- 1:nrow(res)
> >>>>> res
> >>>>>#  m n x y   p2  p1 m1 n1 cterm1_P1L cterm1_P0H
> >>>>>#1 5 4 4 2 0.50 0.8  3  2    0.00032     0.0025
> >>>>>#2 5 4 5 2 0.50 1.0  3  2    0.00032     0.0025
> >>>>>#3 5 4 6 2 0.50 1.2  3  2    0.00032     0.0025
> >>>>>#4 5 4 4 3 0.75 0.8  3  2    0.00032     0.0025
> >>>>>#5 5 4 5 3 0.75 1.0  3  2    0.00032     0.0025
> >>>>>#6 5 4 6 3 0.75 1.2  3  2    0.00032     0.0025
> >>>>>#7 5 4 4 4 1.00 0.8  3  2    0.00032     0.0025
> >>>>>#8 5 4 5 4 1.00 1.0  3  2    0.00032     0.0025
> >>>>>#9 5 4 6 4 1.00 1.2  3  2    0.00032     0.0025
> >>>>>
> >>>>>A.K.
> >>>>>
> >>>>>
> >>>>>
> >>>>>
> >>>>>
> >>>>>----- Original Message -----
> >>>>>From: Zjoanna <[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=14>>
>
> >>>>>To: [hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=15>
> >>>>>Cc:
> >>>>>
> >>>>>Sent: Sunday, February 10, 2013 6:04 PM
> >>>>>Subject: Re: [R] cumulative sum by group and under some criteria
> >>>>>
> >>>>>
> >>>>>Hi,
> >>>>>How to expand or loop for one variable n based on another variable?
> for
> >>>>>example, I want to add m (from m1 to maxN- n1-2) and for each m, I
> want to
> >>>>>add n (n1+2 to maxN-m), and similarly add x and y, then I need to do
> some
> >>>>>calculations.
> >>>>>
> >>>>>d3<-data.frame(d2)
> >>>>>    for (m in (m1+2):(maxN-(n1+2)){
> >>>>>       for (n in (n1+2):(maxN-m)){
> >>>>>             for (x in x1:(x1+m-m1)){
> >>>>>                  for (y in y1:(y1+n-n1)){
> >>>>>                       p1<- x/m
> >>>>>                       p2<- y/n
> >>>>>}}}}
> >>>>>
> >>>>>On Thu, Feb 7, 2013 at 12:16 AM, arun kirshna [via R] <
>  >>>>>[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=16>>
> wrote:
> >>>>>
> >>>>>> Hi,
> >>>>>>
> >>>>>> Anyway, just using some random combinations:
> >>>>>>  dnew<- expand.grid(4:10,5:10,6:10,3:7,4:5,6:8)
> >>>>>> names(dnew)<-c("m","n","x1","y1","x","y")
> >>>>>> resF<- cbind(dnew,d2[rep(1:nrow(d2),nrow(dnew)),])
> >>>>>>
> >>>>>>  row.names(resF)<- 1:nrow(resF)
> >>>>>>  head(resF)
> >>>>>> #  m n x1 y1 x y m1 n1 cterm1_P1L cterm1_P0H
> >>>>>> #1 4 5  6  3 4 6  3  2    0.00032     0.0025
> >>>>>> #2 5 5  6  3 4 6  3  2    0.00032     0.0025
> >>>>>> #3 6 5  6  3 4 6  3  2    0.00032     0.0025
> >>>>>> #4 7 5  6  3 4 6  3  2    0.00032     0.0025
> >>>>>> #5 8 5  6  3 4 6  3  2    0.00032     0.0025
> >>>>>> #6 9 5  6  3 4 6  3  2    0.00032     0.0025
> >>>>>>
> >>>>>>  nrow(resF)
> >>>>>> #[1] 6300
> >>>>>> I am not sure what you want to do with this.
> >>>>>> A.K.
> >>>>>> ________________________________
> >>>>>> From: Joanna Zhang <[hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=0>>
> >>>>>>
> >>>>>> To: arun <[hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=1>>
> >>>>>
> >>>>>>
> >>>>>> Sent: Wednesday, February 6, 2013 10:29 AM
> >>>>>> Subject: Re: cumulative sum by group and under some criteria
> >>>>>>
> >>>>>>
> >>>>>> Hi,
> >>>>>>
> >>>>>> Thanks! I need to do some calculations in the expended data, the
> expended
> >>>>>> data would be very large, what is an efficient way, doing
> calculations
> >>>>>> while expending the data, something similiar with the following, or
> >>>>>> expending data using the code in your message and then add
> calculations in
> >>>>>> the expended data?
> >>>>>>
> >>>>>> d3<-data.frame(d2)
> >>>>>>    for .......{
> >>>>>>          for {
> >>>>>>               for .... {
> >>>>>>                   for .....{
> >>>>>>                        p1<- x/m
> >>>>>>                        p2<- y/n
> >>>>>>                       ..........
> >>>>>> }}
> >>>>>> }}
> >>>>>>
> >>>>>> I also modified your code for expending data:
> >>>>>> dnew<-expand.grid((m1+2):(maxN-(n1+2)),(n1+2):(maxN-m),0:m1,0:n1,
> >>>>>> x1:(x1+m-m1),y1:(y1+n-n1))
> >>>>>> names(dnew)<-c("m","n","x1","y1","x","y")
> >>>>>> dnew
> >>>>>> resF<-cbind(dnew[,c(2,1)],d2[rep(1:nrow(d2),nrow(dnew)),])    #
> this is
> >>>>>> not correct, how to modify it.
> >>>>>> resF
> >>>>>> row.names(resF)<-1:nrow(resF)
> >>>>>> resF
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>> On Tue, Feb 5, 2013 at 2:46 PM, arun <[hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=2>>
> >>>>>
> >>>>>> wrote:
> >>>>>>
> >>>>>> Hi,
> >>>>>>
> >>>>>> >
> >>>>>> >You can reduce the steps to reach d2:
> >>>>>> >res3<-
> >>>>>>
> with(res2,aggregate(cbind(cterm1_P1L,cterm1_P0H),by=list(m1,n1),max))
> >>>>>> >
> >>>>>> >#Change it to:
> >>>>>> >res3new<-  aggregate(.~m1+n1,data=res2[,c(1:2,12:13)],max)
> >>>>>> >res3new
> >>>>>> > m1 n1 cterm1_P1L cterm1_P0H
> >>>>>> >1  2  2    0.01440 0.00273750
> >>>>>> >2  3  2    0.00032 0.00250000
> >>>>>> >3  2  3    0.01952 0.00048125
> >>>>>> >d2<-res3new[res3new[,3]<0.01 & res3new[,4]<0.01,]
> >>>>>> >
> >>>>>> > dnew<-expand.grid(4:10,5:10)
> >>>>>> > names(dnew)<-c("n","m")
> >>>>>> >resF<-cbind(dnew[,c(2,1)],d2[rep(1:nrow(d2),nrow(dnew)),])
> >>>>>> >
> >>>>>> >row.names(resF)<-1:nrow(resF)
> >>>>>> > head(resF)
> >>>>>> >#  m n m1 n1 cterm1_P1L cterm1_P0H
> >>>>>> >#1 5 4  3  2    0.00032     0.0025
> >>>>>> >#2 5 5  3  2    0.00032     0.0025
> >>>>>> >#3 5 6  3  2    0.00032     0.0025
> >>>>>> >#4 5 7  3  2    0.00032     0.0025
> >>>>>> >#5 5 8  3  2    0.00032     0.0025
> >>>>>> >#6 5 9  3  2    0.00032     0.0025
> >>>>>> >
> >>>>>> >A.K.
> >>>>>> >
> >>>>>> >________________________________
> >>>>>> >From: Joanna Zhang <[hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=3>>
> >>>>>>
> >>>>>> >To: arun <[hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=4>>
> >>>>>
> >>>>>>
> >>>>>> >Sent: Tuesday, February 5, 2013 2:48 PM
> >>>>>> >
> >>>>>> >Subject: Re: cumulative sum by group and under some criteria
> >>>>>> >
> >>>>>> >
> >>>>>> >  Hi ,
> >>>>>> >what I want is :
> >>>>>> >m   n    m1    n1 cterm1_P1L   cterm1_P0H
> >>>>>> > 5   4    3       2    0.00032         0.00250000
> >>>>>> > 5   5    3       2    0.00032         0.00250000
> >>>>>> > 5   6    3       2    0.00032         0.00250000
> >>>>>> > 5   7    3       2    0.00032         0.00250000
> >>>>>> > 5   8   3       2    0.00032         0.00250000
> >>>>>> > 5   9   3       2    0.00032         0.00250000
> >>>>>> >5   10  3       2    0.00032         0.00250000
> >>>>>> >6    4   3       2    0.00032         0.00250000
> >>>>>> >6    5   3       2    0.00032         0.00250000
> >>>>>> >6    6   3       2    0.00032         0.00250000
> >>>>>> >6    7   3       2    0.00032         0.00250000
> >>>>>> >.....
> >>>>>> >6    10  3       2    0.00032         0.00250000
> >>>>>> >
> >>>>>> >
> >>>>>> >
> >>>>>> >On Tue, Feb 5, 2013 at 1:12 PM, arun <[hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=5>>
> >>>>>
> >>>>>> wrote:
> >>>>>> >
> >>>>>> >Hi,
> >>>>>> >>
> >>>>>> >>Saw your message on Nabble.
> >>>>>> >>
> >>>>>> >>
> >>>>>> >>"I want to add some more columns based on the results. Is the
> following
> >>>>>> code good way to create such a data frame and How to see the column
> m and n
> >>>>>> in the updated data?
> >>>>>> >>
> >>>>>> >>d2<- reres3[res3[,3]<0.01 & res3[,4]<0.01,]
> >>>>>> >># should be a typo
> >>>>>> >>
> >>>>>> >>colnames(d2)[1:2]<- c("m1","n1");
> >>>>>> >>d2 #already a data.frame
> >>>>>> >>
> >>>>>> >>d3<-data.frame(d2)
> >>>>>> >>   for (m in (m1+2):10){
> >>>>>> >>        for (n in (n1+2):10){
> >>>>>> >> d3<-rbind(d3, c(d2))}}" #this is not making much sense to me.
> >>>>>>  Especially, you mentioned you wanted add more columns.
> >>>>>> >>#Running this step gave error
> >>>>>> >>#Error: object 'm1' not found
> >>>>>> >>
> >>>>>> >>Not sure what you want as output.
> >>>>>> >>Could you show the ouput that is expected:
> >>>>>> >>
> >>>>>> >>A.K.
> >>>>>> >>
> >>>>>> >>
> >>>>>> >>
> >>>>>> >>
> >>>>>> >>
> >>>>>> >>
> >>>>>> >>
> >>>>>> >>
> >>>>>> >>________________________________
> >>>>>> >>From: Joanna Zhang <[hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=6>>
> >>>>>>
> >>>>>> >>To: arun <[hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=7>>
> >>>>>
> >>>>>>
> >>>>>> >>Sent: Tuesday, February 5, 2013 10:23 AM
> >>>>>> >>
> >>>>>> >>Subject: Re: cumulative sum by group and under some criteria
> >>>>>> >>
> >>>>>> >>
> >>>>>> >>Hi,
> >>>>>> >>
> >>>>>> >>Yes, I changed code. You answered the questions. But how can I
> put two
> >>>>>> criteria in the code, if both the maximum value of cterm1_p1L <=
> 0.01 and
> >>>>>> cterm1_p1H <=0.01, the output the m1,n1.
> >>>>>> >>
> >>>>>> >>
> >>>>>> >>
> >>>>>> >>
> >>>>>>  >>On Tue, Feb 5, 2013 at 8:47 AM, arun <[hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=8>>
> >>>>>
> >>>>>> wrote:
> >>>>>> >>
> >>>>>> >>
> >>>>>> >>>
> >>>>>> >>> HI,
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>I am not getting the same results as yours:  You must have
> changed the
> >>>>>> dataset.
> >>>>>> >>> res2[,1:2][res2$cterm1_P1L<0.6 & res2$cterm1_P0H<0.95,]
> >>>>>> >>>   m1 n1
> >>>>>> >>>1   2  2
> >>>>>> >>>2   2  2
> >>>>>> >>>3   2  2
> >>>>>> >>>4   2  2
> >>>>>> >>>5   2  2
> >>>>>> >>>6   2  2
> >>>>>> >>>7   2  2
> >>>>>> >>>8   2  2
> >>>>>> >>>9   2  2
> >>>>>> >>>10  3  2
> >>>>>> >>>11  3  2
> >>>>>> >>>12  3  2
> >>>>>> >>>13  3  2
> >>>>>> >>>14  3  2
> >>>>>> >>>15  3  2
> >>>>>> >>>16  3  2
> >>>>>> >>>17  3  2
> >>>>>> >>>18  3  2
> >>>>>> >>>19  3  2
> >>>>>> >>>20  3  2
> >>>>>> >>>21  3  2
> >>>>>> >>>22  2  3
> >>>>>> >>>23  2  3
> >>>>>> >>>24  2  3
> >>>>>> >>>25  2  3
> >>>>>> >>>26  2  3
> >>>>>> >>>27  2  3
> >>>>>> >>>28  2  3
> >>>>>> >>>29  2  3
> >>>>>> >>>30  2  3
> >>>>>> >>>31  2  3
> >>>>>> >>>32  2  3
> >>>>>> >>>33  2  3
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>Regarding the maximum value within each block, haven't I
> answered in
> >>>>>> the earlier post.
> >>>>>> >>>
> >>>>>> >>>aggregate(cterm1_P1L~m1+n1,data=res2,max)
> >>>>>> >>>#  m1 n1 cterm1_P1L
> >>>>>> >>>#1  2  2    0.01440
> >>>>>> >>>#2  3  2    0.00032
> >>>>>> >>>#3  2  3    0.01952
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>
> with(res2,aggregate(cbind(cterm1_P1L,cterm1_P0H),by=list(m1,n1),max))
> >>>>>> >>>#  Group.1 Group.2 cterm1_P1L cterm1_P0H
> >>>>>> >>>#1       2       2    0.01440 0.00273750
> >>>>>> >>>#2       3       2    0.00032 0.00250000
> >>>>>> >>>#3       2       3    0.01952 0.00048125
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>A.K.
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>----- Original Message -----
> >>>>>
> >>>>>> >>>From: "[hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=9>";;;;;;
> >>>>>> <[hidden email] <
> http://user/SendEmail.jtp?type=node&node=4657773&i=10>>
> >>>>>> >>>To: [hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=11>
> >>>>>>  >>>Cc:
> >>>>>> >>>
> >>>>>> >>>Sent: Tuesday, February 5, 2013 9:33 AM
> >>>>>> >>>Subject: Re: cumulative sum by group and under some criteria
> >>>>>> >>>
> >>>>>> >>>Hi,
> >>>>>> >>>If use this
> >>>>>> >>>
> >>>>>> >>>res2[,1:2][res2$cterm1_P1L<0.6 & res2$cterm1_P0H<0.95,]
> >>>>>> >>>
> >>>>>> >>>the results are the following, but actually only m1=3, n1=2
> sastify the
> >>>>>> criteria, as I need to look at the row with maximum value within
> each
> >>>>>> block,not every row.
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>   m1 n1
> >>>>>> >>>1   2  2
> >>>>>> >>>10  3  2
> >>>>>> >>>11  3  2
> >>>>>> >>>12  3  2
> >>>>>> >>>13  3  2
> >>>>>> >>>14  3  2
> >>>>>> >>>15  3  2
> >>>>>> >>>16  3  2
> >>>>>> >>>17  3  2
> >>>>>> >>>18  3  2
> >>>>>> >>>19  3  2
> >>>>>> >>>20  3  2
> >>>>>> >>>21  3  2
> >>>>>> >>>22  2  3
> >>>>>> >>>23  2  3
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>><quote author='arun kirshna'>
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>Hi,
> >>>>>> >>>Thanks. This extract every row that satisfy the condition, but I
> need
> >>>>>> look
> >>>>>> >>>at the last row (the maximum of cumulative sum) for each block
> (m1,n1).
> >>>>>> for
> >>>>>> >>>example, if I set the criteria
> >>>>>> >>>
> >>>>>> >>>res2$cterm1_P1L<0.6 & res2$cterm1_P0H<0.95, this should extract
> m1= 3,
> >>>>>> n1 =
> >>>>>> >>>2.
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>Hi,
> >>>>>> >>>I am not sure I understand your question.
> >>>>>> >>>res2$cterm1_P1L<0.6 & res2$cterm1_P0H<0.95
> >>>>>> >>> #[1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
> TRUE TRUE
> >>>>>> TRUE
> >>>>>> >>>TRUE
> >>>>>> >>>#[16] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
> TRUE TRUE
> >>>>>> TRUE
> >>>>>> >>>TRUE
> >>>>>> >>>#[31] TRUE TRUE TRUE
> >>>>>> >>>
> >>>>>> >>>This will extract all the rows.
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>res2[,1:2][res2$cterm1_P1L<0.01 & res2$cterm1_P1L!=0,]
> >>>>>> >>>#   m1 n1
> >>>>>> >>>#21  3  2
> >>>>>> >>>This extract only the row you wanted.
> >>>>>> >>>
> >>>>>> >>>For the different groups:
> >>>>>> >>>
> >>>>>> >>>aggregate(cterm1_P1L~m1+n1,data=res2,max)
> >>>>>> >>>#  m1 n1 cterm1_P1L
> >>>>>> >>>#1  2  2    0.01440
> >>>>>> >>>#2  3  2    0.00032
> >>>>>> >>>#3  2  3    0.01952
> >>>>>> >>>
> >>>>>> >>> aggregate(cterm1_P1L~m1+n1,data=res2,function(x) max(x)<0.01)
> >>>>>> >>> # m1 n1 cterm1_P1L
> >>>>>> >>>#1  2  2      FALSE
> >>>>>> >>>#2  3  2       TRUE
> >>>>>> >>>#3  2  3      FALSE
> >>>>>> >>>
> >>>>>> >>>res4<-aggregate(cterm1_P1L~m1+n1,data=res2,function(x)
> max(x)<0.01)
> >>>>>> >>>res4[,1:2][res4[,3],]
> >>>>>> >>>#  m1 n1
> >>>>>> >>>#2  3  2
> >>>>>> >>>
> >>>>>> >>>A.K.
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>----- Original Message -----
> >>>>>
> >>>>>> >>>From: "[hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=12>";;;;;;
> >>>>>> <[hidden email] <
> http://user/SendEmail.jtp?type=node&node=4657773&i=13>>
> >>>>>> >>>To: [hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=14>
> >>>>>>  >>>Cc:
> >>>>>> >>>Sent: Sunday, February 3, 2013 3:58 PM
> >>>>>> >>>Subject: Re: cumulative sum by group and under some criteria
> >>>>>> >>>
> >>>>>> >>>Hi,
> >>>>>> >>>Let me restate my questions. I need to get the m1 and n1 that
> satisfy
> >>>>>> some
> >>>>>> >>>criteria, for example in this case, within each group, the
> maximum
> >>>>>> >>>cterm1_p1L ( the last row in this group) <0.01. I need to
> extract m1=3,
> >>>>>> >>>n1=2, I only need m1, n1 in the row.
> >>>>>> >>>
> >>>>>> >>>Also, how to create the structure from the data.frame, I am new
> to R, I
> >>>>>> need
> >>>>>> >>>to change the maxN and run the loop to different data.
> >>>>>> >>>Thanks very much for your help!
> >>>>>> >>>
> >>>>>> >>><quote author='arun kirshna'>
> >>>>>> >>>HI,
> >>>>>> >>>
> >>>>>> >>>I think this should be more correct:
> >>>>>> >>>maxN<-9
> >>>>>> >>>c11<-0.2
> >>>>>> >>>c12<-0.2
> >>>>>> >>>p0L<-0.05
> >>>>>> >>>p0H<-0.05
> >>>>>> >>>p1L<-0.20
> >>>>>> >>>p1H<-0.20
> >>>>>> >>>
> >>>>>> >>>d <- structure(list(m1 = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
> 2,
> >>>>>> >>>2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3),
> >>>>>> >>>    n1 = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3,
> >>>>>> >>>    3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2), x1 = c(0,
> >>>>>> >>>    0, 0, 1, 1, 1, 2, 2, 2, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2,
> >>>>>> >>>    2, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3), y1 = c(0, 1, 2, 0,
> >>>>>> >>>    1, 2, 0, 1, 2, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1,
> >>>>>> >>>    2, 0, 1, 2, 0, 1, 2, 0, 1, 2), Fmm = c(0, 0, 0, 0.7, 0.59,
> >>>>>> >>>    0.64, 1, 1, 1, 0, 0, 0, 0, 0.63, 0.7, 0.74, 0.68, 1, 1, 1,
> >>>>>> >>>    1, 0, 0, 0, 0.62, 0.63, 0.6, 0.63, 0.6, 0.68, 1, 1, 1), Fnn
> = c(0,
> >>>>>> >>>    0.64, 1, 0, 0.51, 1, 0, 0.67, 1, 0, 0.62, 0.69, 1, 0, 0.54,
> >>>>>> >>>    0.62, 1, 0, 0.63, 0.73, 1, 0, 0.63, 1, 0, 0.7, 1, 0, 0.7,
> >>>>>> >>>    1, 0, 0.58, 1), Qm = c(1, 1, 1, 0.65, 0.45, 0.36, 0.5,
> 0.165,
> >>>>>> >>>    0, 1, 1, 1, 1, 0.685, 0.38, 0.32, 0.32, 0.5, 0.185, 0.135,
> >>>>>> >>>    0, 1, 1, 1, 0.69, 0.37, 0.4, 0.685, 0.4, 0.32, 0.5, 0.21,
> >>>>>> >>>    0), Qn = c(1, 0.36, 0, 0.65, 0.45, 0, 0.5, 0.165, 0, 1,
> 0.38,
> >>>>>> >>>    0.31, 0, 0.685, 0.38, 0.32, 0, 0.5, 0.185, 0.135, 0, 1,
> 0.37,
> >>>>>> >>>    0, 0.69, 0.3, 0, 0.685, 0.3, 0, 0.5, 0.21, 0), term1_p0 =
> >>>>>> c(0.81450625,
> >>>>>> >>>    0.0857375, 0.00225625, 0.0857375, 0.009025, 0.0002375,
> 0.00225625,
> >>>>>> >>>    0.0002375, 6.25e-06, 0.7737809375, 0.1221759375,
> >>>>>> 0.00643031249999999,
> >>>>>> >>>    0.0001128125, 0.081450625, 0.012860625, 0.000676875,
> 1.1875e-05,
> >>>>>> >>>    0.0021434375, 0.0003384375, 1.78125e-05, 3.125e-07,
> 0.7737809375,
> >>>>>> >>>    0.081450625, 0.0021434375, 0.1221759375, 0.012860625,
> >>>>>> 0.0003384375,
> >>>>>> >>>    0.00643031249999999, 0.000676875, 1.78125e-05, 0.0001128125,
> >>>>>> >>>    1.1875e-05, 3.125e-07), term1_p1 = c(0.4096, 0.2048, 0.0256,
> >>>>>> >>>    0.2048, 0.1024, 0.0128, 0.0256, 0.0128, 0.0016, 0.32768,
> >>>>>> >>>    0.24576, 0.06144, 0.00512, 0.16384, 0.12288, 0.03072,
> 0.00256,
> >>>>>> >>>    0.02048, 0.01536, 0.00384, 0.00032, 0.32768, 0.16384,
> 0.02048,
> >>>>>> >>>    0.24576, 0.12288, 0.01536, 0.06144, 0.03072, 0.00384,
> 0.00512,
> >>>>>> >>>    0.00256, 0.00032)), .Names = c("m1", "n1", "x1", "y1",
> "Fmm",
> >>>>>> >>>"Fnn", "Qm", "Qn", "term1_p0", "term1_p1"), row.names = c(NA,
> >>>>>> >>>33L), class = "data.frame")
> >>>>>> >>>
> >>>>>> >>>library(zoo)
> >>>>>> >>>lst1<- split(d,list(d$m1,d$n1))
> >>>>>>
> >>>res2<-do.call(rbind,lapply(lst1[lapply(lst1,nrow)!=0],function(x){
> >>>>>> >>>x[,11:14]<-NA;
> >>>>>> >>>x[,11:12][x$Qm<=c11,]<-cumsum(x[,9:10][x$Qm<=c11,]);
> >>>>>> >>>x[,13:14][x$Qn<=c12,]<-cumsum(x[,9:10][x$Qn<=c12,]);
> >>>>>> >>>colnames(x)[11:14]<-
> >>>>>> c("cterm1_P0L","cterm1_P1L","cterm1_P0H","cterm1_P1H");
> >>>>>> >>>x1<-na.locf(x);
> >>>>>> >>>x1[,11:14][is.na(x1[,11:14])]<-0;
> >>>>>> >>>x1}))
> >>>>>> >>>row.names(res2)<- 1:nrow(res2)
> >>>>>> >>>
> >>>>>> >>> res2
> >>>>>> >>> #  m1 n1 x1 y1  Fmm  Fnn    Qm    Qn     term1_p0 term1_p1
> >>>>>> cterm1_P0L
> >>>>>> >>>cterm1_P1L   cterm1_P0H cterm1_P1H
> >>>>>> >>>
> >>>>>> >>>#1   2  2  0  0 0.00 0.00 1.000 1.000 0.8145062500  0.40960
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0000000000    0.00000
> >>>>>> >>>#2   2  2  0  1 0.00 0.64 1.000 0.360 0.0857375000  0.20480
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0000000000    0.00000
> >>>>>> >>>#3   2  2  0  2 0.00 1.00 1.000 0.000 0.0022562500  0.02560
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0022562500    0.02560
> >>>>>> >>>#4   2  2  1  0 0.70 0.00 0.650 0.650 0.0857375000  0.20480
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0022562500    0.02560
> >>>>>> >>>#5   2  2  1  1 0.59 0.51 0.450 0.450 0.0090250000  0.10240
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0022562500    0.02560
> >>>>>> >>>#6   2  2  1  2 0.64 1.00 0.360 0.000 0.0002375000  0.01280
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0024937500    0.03840
> >>>>>> >>>#7   2  2  2  0 1.00 0.00 0.500 0.500 0.0022562500  0.02560
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0024937500    0.03840
> >>>>>> >>>#8   2  2  2  1 1.00 0.67 0.165 0.165 0.0002375000  0.01280
> >>>>>> 0.0002375000
> >>>>>> >>> 0.01280 0.0027312500    0.05120
> >>>>>> >>>#9   2  2  2  2 1.00 1.00 0.000 0.000 0.0000062500  0.00160
> >>>>>> 0.0002437500
> >>>>>> >>> 0.01440 0.0027375000    0.05280
> >>>>>> >>>#10  3  2  0  0 0.00 0.00 1.000 1.000 0.7737809375  0.32768
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0000000000    0.00000
> >>>>>> >>>#11  3  2  0  1 0.00 0.63 1.000 0.370 0.0814506250  0.16384
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0000000000    0.00000
> >>>>>> >>>#12  3  2  0  2 0.00 1.00 1.000 0.000 0.0021434375  0.02048
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0021434375    0.02048
> >>>>>> >>>#13  3  2  1  0 0.62 0.00 0.690 0.690 0.1221759375  0.24576
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0021434375    0.02048
> >>>>>> >>>#14  3  2  1  1 0.63 0.70 0.370 0.300 0.0128606250  0.12288
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0021434375    0.02048
> >>>>>> >>>#15  3  2  1  2 0.60 1.00 0.400 0.000 0.0003384375  0.01536
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0024818750    0.03584
> >>>>>> >>>#16  3  2  2  0 0.63 0.00 0.685 0.685 0.0064303125  0.06144
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0024818750    0.03584
> >>>>>> >>>#17  3  2  2  1 0.60 0.70 0.400 0.300 0.0006768750  0.03072
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0024818750    0.03584
> >>>>>> >>>#18  3  2  2  2 0.68 1.00 0.320 0.000 0.0000178125  0.00384
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0024996875    0.03968
> >>>>>> >>>#19  3  2  3  0 1.00 0.00 0.500 0.500 0.0001128125  0.00512
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0024996875    0.03968
> >>>>>> >>>#20  3  2  3  1 1.00 0.58 0.210 0.210 0.0000118750  0.00256
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0024996875    0.03968
> >>>>>> >>>#21  3  2  3  2 1.00 1.00 0.000 0.000 0.0000003125  0.00032
> >>>>>> 0.0000003125
> >>>>>> >>> 0.00032 0.0025000000    0.04000
> >>>>>> >>>#22  2  3  0  0 0.00 0.00 1.000 1.000 0.7737809375  0.32768
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0000000000    0.00000
> >>>>>> >>>#23  2  3  0  1 0.00 0.62 1.000 0.380 0.1221759375  0.24576
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0000000000    0.00000
> >>>>>> >>>#24  2  3  0  2 0.00 0.69 1.000 0.310 0.0064303125  0.06144
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0000000000    0.00000
> >>>>>> >>>#25  2  3  0  3 0.00 1.00 1.000 0.000 0.0001128125  0.00512
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0001128125    0.00512
> >>>>>> >>>#26  2  3  1  0 0.63 0.00 0.685 0.685 0.0814506250  0.16384
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0001128125    0.00512
> >>>>>> >>>#27  2  3  1  1 0.70 0.54 0.380 0.380 0.0128606250  0.12288
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0001128125    0.00512
> >>>>>> >>>#28  2  3  1  2 0.74 0.62 0.320 0.320 0.0006768750  0.03072
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0001128125    0.00512
> >>>>>> >>>#29  2  3  1  3 0.68 1.00 0.320 0.000 0.0000118750  0.00256
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0001246875    0.00768
> >>>>>> >>>#30  2  3  2  0 1.00 0.00 0.500 0.500 0.0021434375  0.02048
> >>>>>> 0.0000000000
> >>>>>> >>> 0.00000 0.0001246875    0.00768
> >>>>>> >>>#31  2  3  2  1 1.00 0.63 0.185 0.185 0.0003384375  0.01536
> >>>>>> 0.0003384375
> >>>>>> >>> 0.01536 0.0004631250    0.02304
> >>>>>> >>>#32  2  3  2  2 1.00 0.73 0.135 0.135 0.0000178125  0.00384
> >>>>>> 0.0003562500
> >>>>>> >>> 0.01920 0.0004809375    0.02688
> >>>>>> >>>#33  2  3  2  3 1.00 1.00 0.000 0.000 0.0000003125  0.00032
> >>>>>> 0.0003565625
> >>>>>> >>> 0.01952 0.0004812500    0.02720
> >>>>>> >>>
> >>>>>> >>>#Sorry, some values in my previous solution didn't look right. I
> >>>>>> didn't
> >>>>>> >>>A.K.
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>----- Original Message -----
> >>>>>> >>>From: Zjoanna <[hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=15>>
> >>>>>>
> >>>>>> >>>To: [hidden email]<
> http://user/SendEmail.jtp?type=node&node=4657773&i=16>
> >>>>>
> >>>>>> >>>Cc:
> >>>>>> >>>Sent: Friday, February 1, 2013 12:19 PM
> >>>>>> >>>Subject: Re: [R] cumulative sum by group and under some criteria
> >>>>>> >>>
> >>>>>> >>>Thank you very much for your reply. Your code work well with
> this
> >>>>>> example.
> >>>>>> >>>I modified a little to fit my real data, I got an error massage.
> >>>>>> >>>
> >>>>>> >>>Error in split.default(x = seq_len(nrow(x)), f = f, drop = drop,
> ...) :
> >>>>>> >>>  Group length is 0 but data length > 0
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>On Thu, Jan 31, 2013 at 12:21 PM, arun kirshna [via R] <
> >>>>>>  >>>[hidden email] <
> http://user/SendEmail.jtp?type=node&node=4657773&i=17>>
> >>>>>
> >>>>>> wrote:
> >>>>>> >>>
> >>>>>> >>>> Hi,
> >>>>>> >>>> Try this:
> >>>>>> >>>> colnames(d)<-c("m1","n1","x1","y1","p11","p12")
> >>>>>> >>>> library(zoo)
> >>>>>> >>>> res1<-
> >>>>>> do.call(rbind,lapply(lapply(split(d,list(d$m1,d$n1)),function(x)
> >>>>>> >>>> {x$cp11[x$x1>1]<- cumsum(x$p11[x$x1>1]);x$cp12[x$y1>1]<-
> >>>>>> >>>> cumsum(x$p12[x$y1>1]);x}),function(x)
> >>>>>> >>>> {x$cp11<-na.locf(x$cp11,na.rm=F);x$cp12<-
> >>>>>> na.locf(x$cp12,na.rm=F);x}))
> >>>>>> >>>> #there would be a warning here as one of the list element is
> NULL.
> >>>>>> The,
> >>>>>> >>>> warning is okay
> >>>>>> >>>> row.names(res1)<- 1:nrow(res1)
> >>>>>> >>>> res1[,7:8][is.na(res1[,7:8])]<- 0
> >>>>>> >>>> res1
> >>>>>> >>>>  #  m1 n1 x1 y1  p11  p12 cp11 cp12
> >>>>>> >>>> #1   2  2  0  0 0.00 0.00 0.00 0.00
> >>>>>> >>>> #2   2  2  0  1 0.00 0.50 0.00 0.00
> >>>>>> >>>> #3   2  2  0  2 0.00 1.00 0.00 1.00
> >>>>>> >>>> #4   2  2  1  0 0.50 0.00 0.00 1.00
> >>>>>> >>>> #5   2  2  1  1 0.50 0.50 0.00 1.00
> >>>>>> >>>> #6   2  2  1  2 0.50 1.00 0.00 2.00
> >>>>>> >>>> #7   2  2  2  0 1.00 0.00 1.00 2.00
> >>>>>> >>>> #8   2  2  2  1 1.00 0.50 2.00 2.00
> >>>>>> >>>> #9   2  2  2  2 1.00 1.00 3.00 3.00
> >>>>>> >>>> #10  3  2  0  0 0.00 0.00 0.00 0.00
> >>>>>> >>>> #11  3  2  0  1 0.00 0.50 0.00 0.00
> >>>>>> >>>> #12  3  2  0  2 0.00 1.00 0.00 1.00
> >>>>>> >>>> #13  3  2  1  0 0.33 0.00 0.00 1.00
> >>>>>> >>>> #14  3  2  1  1 0.33 0.50 0.00 1.00
> >>>>>> >>>> #15  3  2  1  2 0.33 1.00 0.00 2.00
> >>>>>> >>>> #16  3  2  2  0 0.67 0.00 0.67 2.00
> >>>>>> >>>> #17  3  2  2  1 0.67 0.50 1.34 2.00
> >>>>>> >>>> #18  3  2  2  2 0.67 1.00 2.01 3.00
> >>>>>> >>>> #19  3  2  3  0 1.00 0.00 3.01 3.00
> >>>>>> >>>> #20  3  2  3  1 1.00 0.50 4.01 3.00
> >>>>>> >>>> #21  3  2  3  2 1.00 1.00 5.01 4.00
> >>>>>> >>>> #22  2  3  0  0 0.00 0.00 0.00 0.00
> >>>>>> >>>> #23  2  3  0  1 0.00 0.33 0.00 0.00
> >>>>>> >>>> #24  2  3  0  2 0.00 0.67 0.00 0.67
> >>>>>> >>>> #25  2  3  0  3 0.00 1.00 0.00 1.67
> >>>>>> >>>> #26  2  3  1  0 0.50 0.00 0.00 1.67
> >>>>>> >>>> #27  2  3  1  1 0.50 0.33 0.00 1.67
> >>>>>> >>>> #28  2  3  1  2 0.50 0.67 0.00 2.34
> >>>>>> >>>> #29  2  3  1  3 0.50 1.00 0.00 3.34
> >>>>>> >>>> #30  2  3  2  0 1.00 0.00 1.00 3.34
> >>>>>> >>>> #31  2  3  2  1 1.00 0.33 2.00 3.34
> >>>>>> >>>> #32  2  3  2  2 1.00 0.67 3.00 4.01
> >>>>>> >>>> #33  2  3  2  3 1.00 1.00 4.00 5.01
> >>>>>> >>>> A.K.
> >>>>>> >>>>
> >>>>>> >>>> ------------------------------
> >>>>>> >>>>  If you reply to this email, your message will be added to the
> >>>>>> discussion
> >>>>>> >>>> below:
> >>>>>> >>>>
> >>>>>> >>>>
> >>>>>>
> http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4657196.html
> >>>>>> >>>> To unsubscribe from cumulative sum by group and under some
> criteria,
> >>>>>> click
> >>>>>> >>>> here<
> >>>>>>
> >>>>>> >>>> .
> >>>>>> >>>> NAML<
> >>>>>>
> http://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=macro_viewer&id=instant_html%21nabble%3Aemail.naml&base=nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.view.web.template.NodeNamespace&breadcrumbs=notify_subscribers%21nabble%3Aemail.naml-instant_emails%21nabble%3Aemail.naml-send_instant_email%21nabble%3Aemail.naml>
>
> >>>>>>
> >>>>>> >>>>
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>--
> >>>>>> >>>View this message in context:
> >>>>>> >>>
> >>>>>>
> http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4657315.html
> >>>>>> >>>Sent from the R help mailing list archive at Nabble.com.
> >>>>>> >>>    [[alternative HTML version deleted]]
> >>>>>> >>>
> >>>>>> >>>______________________________________________
> >>>>>> >>>[hidden email] <
> http://user/SendEmail.jtp?type=node&node=4657773&i=18>mailing list
> >>>>>
> >>>>>> >>>https://stat.ethz.ch/mailman/listinfo/r-help
> >>>>>> >>>PLEASE do read the posting guide
> >>>>>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> <http://www.r-project.org/posting-guide.html>
> >>>>>
> >>>>>> >>>and provide commented, minimal, self-contained, reproducible
> code.
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>______________________________________________
> >>>>>> >>>[hidden email] <
> http://user/SendEmail.jtp?type=node&node=4657773&i=19>mailing list
> >>>>>
> >>>>>> >>>https://stat.ethz.ch/mailman/listinfo/r-help
> >>>>>> >>>PLEASE do read the posting guide
> >>>>>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> <http://www.r-project.org/posting-guide.html>
> >>>>>
> >>>>>> >>>and provide commented, minimal, self-contained, reproducible
> code.
> >>>>>> >>>
> >>>>>> >>></quote>
> >>>>>> >>>Quoted from:
> >>>>>> >>>
> >>>>>>
> http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4657360.html
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>>______________________________________________
> >>>>>> >>>[hidden email] <
> http://user/SendEmail.jtp?type=node&node=4657773&i=20>mailing list
> >>>>>
> >>>>>> >>>https://stat.ethz.ch/mailman/listinfo/r-help
> >>>>>> >>>PLEASE do read the posting guide
> >>>>>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> <http://www.r-project.org/posting-guide.html>
> >>>>>
> >>>>>> >>>and provide commented, minimal, self-contained, reproducible
> code.
> >>>>>> >>>
> >>>>>> >>></quote>
> >>>>>> >>>Quoted from:
> >>>>>> >>>
> >>>>>>
> http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4657582.html
> >>>>>> >>>
> >>>>>> >>>
> >>>>>> >>
> >>>>>> >
> >>>>>>
> >>>>>> ______________________________________________
> >>>>>> [hidden email] <
> http://user/SendEmail.jtp?type=node&node=4657773&i=21>mailing list
> >>>>>
> >>>>>> https://stat.ethz.ch/mailman/listinfo/r-help
> >>>>>> PLEASE do read the posting guide
> >>>>>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> <http://www.r-project.org/posting-guide.html>
> >>>>>
> >>>>>> and provide commented, minimal, self-contained, reproducible code.
> >>>>>>
> >>>>>>
> >>>>>
> >>>>>> ------------------------------
> >>>>>>   If you reply to this email, your message will be added to the
> >>>>>> discussion below:
> >>>>>>
> >>>>>
> >>>>>>
> http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4657773.html
> >>>>>> To unsubscribe from cumulative sum by group and under some
> criteria, click
> >>>>>> here<
>
> >>>>>
> >>>>>> .
> >>>>>> NAML<
> http://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=macro_viewer&id=instant_html%21nabble%3Aemail.naml&base=nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.view.web.template.NodeNamespace&breadcrumbs=notify_subscribers%21nabble%3Aemail.naml-instant_emails%21nabble%3Aemail.naml-send_instant_email%21nabble%3Aemail.naml>
>
> >>>>>>
> >>>>>
> >>>>>
> >>>>>
> >>>>>
> >>>>>--
> >>>>>View this message in context:
> http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4658133.html
> >>>>>
> >>>>>Sent from the R help mailing list archive at Nabble.com.
> >>>>>    [[alternative HTML version deleted]]
> >>>>>
> >>>>>______________________________________________
> >>>>>[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=17>mailing list
> >>>>>
> >>>>>https://stat.ethz.ch/mailman/listinfo/r-help
> >>>>>PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> >>>>>and provide commented, minimal, self-contained, reproducible code.
> >>>>>
> >>>>>
> >>>>
> >>>
> >>
> >
>
> ______________________________________________
> [hidden email] <http://user/SendEmail.jtp?type=node&node=4659515&i=18>mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> and provide commented, minimal, self-contained, reproducible code.
>
>
> ------------------------------
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