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 <zjoanna2...@gmail.com>
To: arun <smartpink...@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 <smartpink...@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 <zjoanna2...@gmail.com>
>To: arun <smartpink...@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 <smartpink...@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 <zjoanna2...@gmail.com>
>>To: arun <smartpink...@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$Qn2<-(1-Fnn_f2)
>>detach(res2)
>>res2
>>head(res2)
>>
>>
>>
>>On Tue, Feb 19, 2013 at 4:09 PM, arun <smartpink...@yahoo.com> wrote:
>>
>>Hi,
>>>
>>>""suppose that I have a dataset 'd'
>>> m1 n1 A B C D
>>>1 2 2 0.902500 0.640 0.9025 0.64
>>>2 3 2 0.857375 0.512 0.9025 0.64
>>>I want to add x1 (from 0 to m1), y1(from 0 to n1), m (range from
>>>m1+2 to 7-n1), n(from n1+2 to 9-m), x (x1 to x1+m-m1), y(y1 to y1+n-n1),
>>>expanding to another dataset 'd2' based on each row (combination of m1
>>>and n1)""
>>>
>>>
>>>Try:
>>>
>>>
>>> d<-read.table(text="
>>>
>>>m1 n1 A B C D
>>>1 2 2 0.902500 0.640 0.9025 0.64
>>>2 3 2 0.857375 0.512 0.9025 0.64
>>>",sep="",header=TRUE)
>>>
>>>vec1<- paste(d[,1],d[,2],d[,3],d[,4],d[,5],d[,6])
>>>res1<- do.call(rbind,lapply(vec1,function(m1)
>>>do.call(rbind,lapply(0:(as.numeric(substr(m1,1,1))),function(x1)
>>>do.call(rbind,lapply(0:(as.numeric(substr(m1,3,3))),function(y1)
>>>do.call(rbind,lapply((as.numeric(substr(m1,1,1))+2):(7-as.numeric(substr(m1,3,3))),function(m)
>>> do.call(rbind,lapply((as.numeric(substr(m1,3,3))+2):(9-m),function(n)
>>>
>>> do.call(rbind,lapply(x1:(x1+m-as.numeric(substr(m1,1,1))), function(x)
>>> do.call(rbind,lapply(y1:(y1+n-as.numeric(substr(m1,3,3))), function(y)
>>> expand.grid(m1,x1,y1,m,n,x,y)) )))))))))))))
>>>
>>names(res1)<- c("group","x1","y1","m","n","x","y")
>>> res1$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 <zjoanna2...@gmail.com>
>>>To: arun <smartpink...@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 <smartpink...@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 <zjoanna2...@gmail.com>
>>>>To: arun <smartpink...@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 <zjoanna2...@gmail.com>
>>>>>To: r-help@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+s789695n4657773...@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)
>>>>>> 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
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