The values of 'x' an 'm' from res2. For more information, you can check ?rbeta.
I also don't get what you are up to.
If you want to create 1000 random samples for each combinations of x, m
lapply(lapply(unique(apply(cbind(res2$x,res2$m),1,paste,collapse="")),function(i)
as.numeric(unlist(strsplit(i,"")))),function(x)
rbeta(1000,0.2+x[1],0.8+x[2]-x[1]))
A.K.
________________________________
From: Joanna Zhang <zjoanna2...@gmail.com>
To: arun <smartpink...@yahoo.com>
Sent: Tuesday, February 26, 2013 10:37 PM
Subject: Re: [R] cumulative sum by group and under some criteria
I don't get it What values of x and m are used here? I thought it should
create 1000 random samples from the beta distribution for each combination of
x,m in the data and this is what I wanted.
In the code, it is creating 1000 values in total from the combination of values
from x, m,
Pm2<-rbeta(1000, 0.2+res2$x, 0.8+res2$m-res2$x)
length(Pm2)
#[1] 1000
On Tue, Feb 26, 2013 at 8:56 PM, arun <smartpink...@yahoo.com> wrote:
??
>
>
>
>________________________________
> From: Joanna Zhang <zjoanna2...@gmail.com>
>To: arun <smartpink...@yahoo.com>
>Sent: Tuesday, February 26, 2013 9:51 PM
>
>Subject: Re: [R] cumulative sum by group and under some criteria
>
>
>
>Hi,
>
>#
>Pm2<-rbeta(1000, 0.2+1, 0.8+3) #obs4
>this is for x=1, m=2
>
> length(Pm2)
>>#[1] 1000
>>
>>
>>Pn2<-rbeta(1000, 0.2, 0.8+4)
>> length(Pn2)
>>#[1] 1000
>>Here, you are creating Pm2 or Pn2 from a single observation.
>>
>>In the code, it is creating 1000 values in total from the combination of
>>values from x, m,
>> Pm2<-rbeta(1000, 0.2+res2$x, 0.8+res2$m-res2$x)
>> length(Pm2)
>>#[1] 1000
>>
>>I don't get it here. What values of x and m are used here? I thought it
>>should create 1000 observations for each combination of x,m in the data and
>>this is what I want.
>>
>
>A.K.
>>
>>
>>
>>----- Original Message -----
>>
>>From: Zjoanna <zjoanna2...@gmail.com>
>>To: r-help@r-project.org
>>Cc:
>>
>>Sent: Tuesday, February 26, 2013 3:13 PM
>>Subject: Re: [R] cumulative sum by group and under some criteria
>>
>>
>>Hi Arun
>>
>>I noticed that the values of Fmm, Fnn, and other corresponding variables
>>are not correct, for example, for the 4th obs after you run this code, the
>>Fmm is 0.40, but if you use the x, m, y, n in the 4th row to calculate
>>them, the results are not consistent, same for the 5th obs.
>>
>>#check
>>#
>>Pm2<-rbeta(1000, 0.2+1, 0.8+3) #obs4
>>Pn2<-rbeta(1000, 0.2, 0.8+4)
>>Fm2<- ecdf(Pm2)
>>Fn2<- ecdf(Pn2)
>>Fmm2<-Fm2(1/4)
>>Fnn2<-Fn2(0)
>>Fmm2 #0.582
>>Fnn2 #0
>>
>>
>>Pm2<-rbeta(1000, 0.2+1, 0.8+3) #obs5
>>Pn2<-rbeta(1000, 0.2+1, 0.8+3)
>>Fm2<- ecdf(Pm2)
>>Fn2<- ecdf(Pn2)
>>Fmm2<-Fm2(1/4)
>>Fnn2<-Fn2(1/4)
>>Fmm2 #0.404
>>Fnn2 #0.416
>>
>>
>>
>>On Sat, Feb 23, 2013 at 10:53 PM, arun kirshna [via R] <
>>ml-node+s789695n4659514...@n4.nabble.com> wrote:
>>
>>> Hi,
>>> 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")
>>> #or
>>>
>>> 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)
>>>
>>> library(plyr)
>>> res2<- join(res1,d3,by=c("m1","n1"),type="inner")
>>>
>>> #Assuming that these are the values you used:
>>>
>>> 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(240, 0.2+x,
>>> 0.8+m-x);Pn2<-rbeta(240, 0.2+y, 0.8+n-y)})
>>> Fm2<- ecdf(res2$Pm2)
>>> Fn2<- ecdf(res2$Pn2)
>>>
>>> res3<- within(res2,{Fmm2<-Fm2(p1);Fnn2<- Fn2(p2);R2<- (Fmm2+Fnn2)/2}) #not
>>> sure about this step especially the Fm2() or Fn2()
>>> res3$Fmm_f2<-apply(res3[,c("R2","Fmm2")],1,min)
>>> res3$Fnn_f2<-apply(res3[,c("R2","Fnn2")],1,max)
>>> res3<- within(res3,{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
>>> Pn2
>>> #1 2 2 0 0 4 4 0 0 0.9025 0.64 0.9025 0.64
>>> 0.001084648
>>> #2 2 2 0 0 4 4 0 1 0.9025 0.64 0.9025 0.64
>>> 0.504593909
>>> #3 2 2 0 0 4 4 0 2 0.9025 0.64 0.9025 0.64
>>> 0.541379357
>>> #4 2 2 0 0 4 4 1 0 0.9025 0.64 0.9025 0.64
>>> 0.138947785
>>> #5 2 2 0 0 4 4 1 1 0.9025 0.64 0.9025 0.64
>>> 0.272364957
>>> #6 2 2 0 0 4 4 1 2 0.9025 0.64 0.9025 0.64
>>> 0.761635059
>>> # Pm2 term2_p1 term2_p0 p2 p1 R2 Fnn2 Fmm2
>>> #1 1.212348e-05 0.16777216 0.6634204313 0.00 0.00 0.0000000 0.0000000 0.0
>>> #2 1.007697e-03 0.08388608 0.0698337296 0.25 0.00 0.1791667 0.3583333 0.0
>>> #3 1.106946e-05 0.01048576 0.0018377297 0.50 0.00 0.3479167 0.6958333 0.0
>>> # 2.086758e-01 0.08388608 0.0698337296 0.00 0.25 0.2000000 0.0000000 0.4
>>> #5 2.382179e-01 0.04194304 0.0073509189 0.25 0.25 0.3791667 0.3583333 0.4
>>> #6 4.494673e-01 0.00524288 0.0001934452 0.50 0.25 0.5479167 0.6958333 0.4
>>> # Fmm_f2 Fnn_f2 Qn2 Qm2
>>> #1 0.0000000 0.0000000 1.0000000 1.0000000
>>> #2 0.0000000 0.3583333 0.6416667 1.0000000
>>> #3 0.0000000 0.6958333 0.3041667 1.0000000
>>> #4 0.2000000 0.2000000 0.8000000 0.8000000
>>> #5 0.3791667 0.3791667 0.6208333 0.6208333
>>> #6 0.4000000 0.6958333 0.3041667 0.6000000
>>>
>>>
>>> A.K.
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>> ________________________________
>>> From: Joanna Zhang <[hidden
>>> email]<http://user/SendEmail.jtp?type=node&node=4659514&i=0>>
>>>
>>> To: arun <[hidden
>>> email]<http://user/SendEmail.jtp?type=node&node=4659514&i=1>>
>>
>>>
>>> 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$Qn2<-(1-Fnn_f2)
>>> detach(res2)
>>> res2
>>> head(res2)
>>>
>>>
>>>
>>> On Tue, Feb 19, 2013 at 4:09 PM, arun <[hidden
>>> email]<http://user/SendEmail.jtp?type=node&node=4659514&i=2>>
>>
>>> wrote:
>>>
>>> Hi,
>>>
>>> >
>>> >""suppose that I have a dataset 'd'
>>> > m1 n1 A B C D
>>> >1 2 2 0.902500 0.640 0.9025 0.64
>>> >2 3 2 0.857375 0.512 0.9025 0.64
>>> >I want to add x1 (from 0 to m1), y1(from 0 to n1), m (range from
>>> >m1+2 to 7-n1), n(from n1+2 to 9-m), x (x1 to x1+m-m1), y(y1 to y1+n-n1),
>>> expanding to another dataset 'd2' based on each row (combination of m1
>>> >and n1)""
>>> >
>>> >
>>> >Try:
>>> >
>>> >
>>> > d<-read.table(text="
>>> >
>>> >m1 n1 A B C D
>>> >1 2 2 0.902500 0.640 0.9025 0.64
>>> >2 3 2 0.857375 0.512 0.9025 0.64
>>> >",sep="",header=TRUE)
>>> >
>>> >vec1<- paste(d[,1],d[,2],d[,3],d[,4],d[,5],d[,6])
>>> >res1<- do.call(rbind,lapply(vec1,function(m1)
>>> do.call(rbind,lapply(0:(as.numeric(substr(m1,1,1))),function(x1)
>>> do.call(rbind,lapply(0:(as.numeric(substr(m1,3,3))),function(y1)
>>> do.call(rbind,lapply((as.numeric(substr(m1,1,1))+2):(7-as.numeric(substr(m1,3,3))),function(m)
>>> do.call(rbind,lapply((as.numeric(substr(m1,3,3))+2):(9-m),function(n)
>>> >
>>> > do.call(rbind,lapply(x1:(x1+m-as.numeric(substr(m1,1,1))), function(x)
>>> > do.call(rbind,lapply(y1:(y1+n-as.numeric(substr(m1,3,3))), function(y)
>>> > expand.grid(m1,x1,y1,m,n,x,y)) )))))))))))))
>>> >
>>> names(res1)<- c("group","x1","y1","m","n","x","y")
>>>
>>> > res1$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=4659514&i=3>>
>>>
>>> >To: arun <[hidden
>>> >email]<http://user/SendEmail.jtp?type=node&node=4659514&i=4>>
>>
>>>
>>> >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=4659514&i=5>>
>>
>>> 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=4659514&i=6>>
>>>
>>> >>To: arun <[hidden
>>> >>email]<http://user/SendEmail.jtp?type=node&node=4659514&i=7>>
>>
>>>
>>> >>
>>> >>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=4659514&i=8>>
>>>
>>> >>>To: [hidden email]<http://user/SendEmail.jtp?type=node&node=4659514&i=9>
>>
>>> >>>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=4659514&i=10>>
>>
>>> 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.
>>> >>>> >>>>
>>> >>>> >>>> ------------------------------
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>>> >>>Sent from the R help mailing list archive at Nabble.com.
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>>> >>>______________________________________________
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