# [R] cumulative sum by group and under some criteria

arun smartpink111 at yahoo.com
Sun Feb 24 00:18:02 CET 2013

```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})
#  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 <zjoanna2013 at gmail.com>
To: arun <smartpink111 at yahoo.com>
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 <smartpink111 at yahoo.com> 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 <zjoanna2013 at gmail.com>
>To: arun <smartpink111 at yahoo.com>
>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 <smartpink111 at yahoo.com> 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 <zjoanna2013 at gmail.com>
>>To: arun <smartpink111 at yahoo.com>
>>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
>>
>>
>>
>>On Tue, Feb 19, 2013 at 4:09 PM, arun <smartpink111 at yahoo.com> 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:
>>>
>>>
>>>
>>>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
>>>
>>>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)]
>>>
>>>
>>>#  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 <zjoanna2013 at gmail.com>
>>>To: arun <smartpink111 at yahoo.com>
>>>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 <smartpink111 at yahoo.com> 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 <zjoanna2013 at gmail.com>
>>>>To: arun <smartpink111 at yahoo.com>
>>>>
>>>>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 <Zjoanna2013 at gmail.com>
>>>>>To: r-help at r-project.org
>>>>>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] <
>>>>>ml-node+s789695n4657773h74 at n4.nabble.com> 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)
>>>>>> #  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)
>>>>>> >#  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
>>>>>> >>
>>>>>> >>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.
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```