[R] cumulative sum by group and under some criteria
arun
smartpink111 at yahoo.com
Sat Mar 2 23:00:13 CET 2013
f1<- function(dat){
stopifnot(nrow(dat)!=0)
do.call(rbind,lapply(unique(dat$m1),function(m1)
do.call(rbind,lapply(unique(dat$n1),function(n1)
do.call(rbind,lapply(unique(dat$x1),function(x1)
do.call(rbind,lapply(unique(dat$y1),function(y1)
#do.call(rbind,lapply(0:m1,function(x1)
#do.call(rbind,lapply(0:n1,function(y1)
do.call(rbind,lapply((m1+2):(maxN-2-n1),function(m)
do.call(rbind,lapply((n1+2):(maxN-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)) )))))))))))))))
}
f1(d4)
#Error: nrow(dat) != 0 is not TRUE
head(f1(d3),2)
# Var1 Var2 Var3 Var4 Var5 Var6 Var7 Var8
#1 3 2 0 0 5 4 0 0
#2 3 2 0 0 5 4 0 1
A.K.
________________________________
From: Joanna Zhang <zjoanna2013 at gmail.com>
To: arun <smartpink111 at yahoo.com>
Sent: Saturday, March 2, 2013 4:47 PM
Subject: Re: [R] cumulative sum by group and under some criteria
got it. is there a way to exit the loop if there is no row (empty data) in d3new?
On Sat, Mar 2, 2013 at 3:38 PM, arun <smartpink111 at yahoo.com> wrote:
HI,
>d
>
># m1 n1 x1 y1 term1_p0 term1_p1
>#1 3 2 0 0 0.7737809375 0.2373046875
>#2 3 2 0 1 0.0814506250 0.1582031250
>#3 3 2 0 2 0.0021434375 0.0263671875
>#4 3 2 1 0 0.1221759375 0.2373046875
>#5 3 2 1 1 0.0128606250 0.1582031250
>#6 3 2 1 2 0.0003384375 0.0263671875
>#7 3 2 2 0 0.0064303125 0.0791015625
>#8 3 2 2 1 0.0006768750 0.0527343750
>#9 3 2 2 2 0.0000178125 0.0087890625
>#10 3 2 3 0 0.0001128125 0.0087890625
>#11 3 2 3 1 0.0000118750 0.0058593750
>#12 3 2 3 2 0.0000003125 0.0009765625
>
>d2
># m1 n1 x1 y1 term1_p0 term1_p1 Qm Qn
>#1 3 2 0 0 0.7737809375 0.2373046875 0.0500 0.0810
>#2 3 2 0 1 0.0814506250 0.1582031250 0.0560 0.6690
>#3 3 2 0 2 0.0021434375 0.0263671875 0.0410 0.9680
>#4 3 2 1 0 0.1221759375 0.2373046875 0.3150 0.3150
>#5 3 2 1 1 0.0128606250 0.1582031250 0.5200 0.6580
>#6 3 2 1 2 0.0003384375 0.0263671875 0.5360 0.9640
>#7 3 2 2 0 0.0064303125 0.0791015625 0.4945 0.4945
>#8 3 2 2 1 0.0006768750 0.0527343750 0.7815 0.7815
>#9 3 2 2 2 0.0000178125 0.0087890625 0.9030 0.9650
>#10 3 2 3 0 0.0001128125 0.0087890625 0.5350 0.5350
>#11 3 2 3 1 0.0000118750 0.0058593750 0.8195 0.8195
>#12 3 2 3 2 0.0000003125 0.0009765625 0.9835 0.9835
>
> lst1<- split(d2,list(d2$m1,d2$n1))
>d3<- do.call(rbind,lapply(lst1[lapply(lst1,nrow)!=0],function(x){
>
>x[,9:14]<-NA;
>x[,9:10][x$Qm<=c11,]<-cumsum(x[,5:6][x$Qm<=c11,]);
>x[,11:12][x$Qn<=c12,]<-cumsum(x[,5:6][x$Qn<=c12,]);
>x[,13:14]<-cumsum(x[,5:6]);
>colnames(x)[9:14]<- c("cterm1_P0L","cterm1_P1L","cterm1_P0H","cterm1_P1H","sumTerm1_p0","sumTerm1_p1");
>x1<-na.locf(x);
>x1[,9:14][is.na(x1[,9:14])]<-0;
>x1}
>))
> row.names(d3)<-1:nrow(d3)
>
>res1<-aggregate(.~m1+n1,data=d3[,c(1:2,9:12)],max)
>res1
># m1 n1 cterm1_P0L cterm1_P1L cterm1_P0H cterm1_P1H
>#1 3 2 0.9795509 0.6591797 0.8959569 0.4746094
> d3New<- res1[res1[,4]<=0.60 & res1[,6]<0.40,]
>d3New
>#[1] m1 n1 cterm1_P0L cterm1_P1L cterm1_P0H cterm1_P1H # zero 0 rows
>#<0 rows> (or 0-length row.names)
> library(plyr)
> d4<-join(d3New,d,by=c("m1","n1"),type="inner")
> d4
># [1] m1 n1 cterm1_P0L cterm1_P1L cterm1_P0H cterm1_P1H #zero 0 rows
># [7] x1 y1 term1_p0 term1_p1
>#<0 rows> (or 0-length row.names)
>
>do.call(rbind,lapply(unique(d4$m1),function(m1)
>
> do.call(rbind,lapply(unique(d4$n1),function(n1)
> do.call(rbind,lapply(unique(d4$x1),function(x1)
> do.call(rbind,lapply(unique(d4$y1),function(y1)
>
> #do.call(rbind,lapply(0:m1,function(x1)
> #do.call(rbind,lapply(0:n1,function(y1)
> do.call(rbind,lapply((m1+2):(maxN-2-n1),function(m)
> do.call(rbind,lapply((n1+2):(maxN-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)) )))))))))))))))
>#NULL
>
>
>
>
>
>A.K.
>________________________________
>From: Joanna Zhang <zjoanna2013 at gmail.com>
>To: arun <smartpink111 at yahoo.com>
>Sent: Saturday, March 2, 2013 3:59 PM
>
>Subject: Re: [R] cumulative sum by group and under some criteria
>
>
>I can't figure out why there is an error for names (): Error in names(res2) <- c("m1", "n1", "x1", "y1", "m", "n", "x", "y") :
> attempt to set an attribute on NULL
>
>
>
>
>maxN<-9
>c11<-0.4
>c12<-0.4
>c1<-0.5
>c2<-0.5
>
>p0L<-0.05
>p0H<-0.05
>p1L<-0.25
>p1H<-0.25
>
>alpha<-0.20
>beta<-0.80
>
>result <- vector("list",5)
>result
>
>for (a in 2: (maxN-6)) {
>d <- data.frame ()
>for ( m1 in a:a) {
> for (n1 in 2: (maxN-m1-4)){
> for (x1 in 0: m1) {
> for (y1 in 0: n1) {
>
>
> term1_p0 = dbinom(x1,m1, p0L, log=FALSE)* dbinom(y1,n1,p0H, log=FALSE)
> term1_p1 = dbinom(x1,m1, p1L, log=FALSE)* dbinom(y1,n1,p1H, log=FALSE)
>
> d<-rbind(d, c(m1,n1,x1,y1,term1_p0,term1_p1))
>}}
>}}
>colnames(d)<-c("m1","n1","x1","y1","term1_p0","term1_p1")
>tail(d)
>
>set.seed(8)
>d1<-do.call(rbind,lapply(seq_len(nrow(d)),function(i){
>Pm<- rbeta(1000,0.2+d[i,"x1"],0.8+d[i,"m1"]-d[i,"x1"]);
>Pn<- rbeta(1000,0.2+d[i,"y1"],0.8+d[i,"n1"]-d[i,"y1"]);
>Fm<- ecdf(Pm);
>Fn<- ecdf(Pn);
>#Fmm<- Fm(d[i,"p11"]);
>#Fnn<- Fn(d[i,"p12"]);
>
>Fmm<- Fm(p1L);
>Fnn<- Fn(p1H);
>
>R<- (Fmm+Fnn)/2;
>Fmm_f<- max(R, Fmm);
>Fnn_f<- min(R, Fnn);
>Qm<- 1-Fmm_f;
>Qn<- 1-Fnn_f;
>data.frame(Qm,Qn)}))
>d2<-cbind(d,d1)
>head(d2)
>
>
>library(zoo)
>lst1<- split(d2,list(d$m1,d$n1))
>d2<-do.call(rbind,lapply(lst1[lapply(lst1,nrow)!=0],function(x){
>x[,9:14]<-NA;
>x[,9:10][x$Qm<=c11,]<-cumsum(x[,5:6][x$Qm<=c11,]);
>x[,11:12][x$Qn<=c12,]<-cumsum(x[,5:6][x$Qn<=c12,]);
>x[,13:14]<-cumsum(x[,5:6]);
>colnames(x)[9:14]<- c("cterm1_P0L","cterm1_P1L","cterm1_P0H","cterm1_P1H","sumTerm1_p0","sumTerm1_p1");
>x1<-na.locf(x);
>x1[,9:14][is.na(x1[,9:14])]<-0;
>x1}
>))
>row.names(d2)<-1:nrow(d2)
>tail(d2)
>
>res1<-aggregate(.~m1+n1,data=d2[,c(1:2,9:12)],max)
>head(res1)
>
>d3<-res1[res1[,4]<=0.60 & res1[,6]<0.40,]
>tail(d3)
>
>library(plyr)
>d4<- join(d3,d,by=c("m1","n1"),type="inner")
>head(d4)
>tail(d4)
>
>res2<-do.call(rbind,lapply(unique(d4$m1),function(m1)
>do.call(rbind,lapply(unique(d4$n1),function(n1)
>do.call(rbind,lapply(unique(d4$x1),function(x1)
>do.call(rbind,lapply(unique(d4$y1),function(y1)
>
>#do.call(rbind,lapply(0:m1,function(x1)
>#do.call(rbind,lapply(0:n1,function(y1)
>do.call(rbind,lapply((m1+2):(maxN-2-n1),function(m)
>do.call(rbind,lapply((n1+2):(maxN-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(res2)<- c("m1","n1","x1","y1","m","n","x","y")
>attr(res2,"out.attrs")<-NULL
>tail(res2)
>result[[a]]<-res2
>}
>result
>
>
>
>
>On Sat, Mar 2, 2013 at 1:05 PM, arun <smartpink111 at yahoo.com> wrote:
>
>Alright, then go ahead and use a loop.
>>
>>A.K.
>>
>>
>>
>>
>>
>>
>>________________________________
>>From: Joanna Zhang <zjoanna2013 at gmail.com>
>>To: arun <smartpink111 at yahoo.com>
>>Sent: Saturday, March 2, 2013 1:53 PM
>>
>>Subject: Re: [R] cumulative sum by group and under some criteria
>>
>>
>>Thank you! When I run my real data, there was a warning massage 'lack of memory'. I am thinking that I can use a loop to run the same code for each part of the data. But I need to keep each output data "d2" and combine them.
>>
>>for example:
>>
>>maxN<-9
>>c11<-0.4
>>c12<-0.4
>>
>>p0L<-0.05
>>p0H<-0.05
>>p1L<-0.25
>>p1H<-0.25
>>
>>
>>for (a in 2: (maxN-6)) {
>>d <- data.frame ()
>>for ( m1 in a:a) {
>> for (n1 in 2: (maxN-m1-4)){
>> for (x1 in 0: m1) {
>> for (y1 in 0: n1) {
>> p11<- (x1/m1)
>> p12<- (y1/n1)
>>
>> term1_p0 = dbinom(x1,m1, p0L, log=FALSE)* dbinom(y1,n1,p0H, log=FALSE)
>> term1_p1 = dbinom(x1,m1, p1L, log=FALSE)* dbinom(y1,n1,p1H, log=FALSE)
>>
>> d<-rbind(d, c(m1,n1,x1,y1,p11,p12,term1_p0,term1_p1))
>>}}
>>}}
>>colnames(d)<-c("m1","n1","x1","y1","p11","p12","term1_p0","term1_p1")
>>tail(d)
>>
>>set.seed(8)
>>d1<-do.call(rbind,lapply(seq_len(nrow(d)),function(i){
>>Pm<- rbeta(1000,0.2+d[i,"x1"],0.8+d[i,"m1"]-d[i,"x1"]);
>>Pn<- rbeta(1000,0.2+d[i,"y1"],0.8+d[i,"n1"]-d[i,"y1"]);
>>Fm<- ecdf(Pm);
>>Fn<- ecdf(Pn);
>>
>>Fmm<- Fm(p1L);
>>Fnn<- Fn(p1H);
>>
>>R<- (Fmm+Fnn)/2;
>>Fmm_f<- max(R, Fmm);
>>Fnn_f<- min(R, Fnn);
>>Qm<- 1-Fmm_f;
>>Qn<- 1-Fnn_f;
>>data.frame(Qm,Qn)}))
>>d2<-cbind(d,d1)
>>head(d2) # need to name "d2" using the value of a (or another way) to distinguish from each other
>>}
>>
>># combine all "d2" here
>>
>>
>>
>>On Fri, Mar 1, 2013 at 12:51 PM, arun <smartpink111 at yahoo.com> wrote:
>>
>>
>>>
>>>Hi,
>>>
>>>It seems like you haven't even looked at the output of d2, (first d2)
>>>d2<- cbind(d,d1)
>>>head(d2,3)
>>># m1 n1 x1 y1 p11 p12 term1_p0 term1_p1 Qm Qn
>>>#1 2 2 0 0 0 0.0 0.81450625 0.31640625 1.000 1.000
>>>#2 2 2 0 1 0 0.5 0.08573750 0.21093750 0.666 0.666
>>>#3 2 2 0 2 0 1.0 0.00225625 0.03515625 0.500 0.500
>>> ncol(d2) # you have only 10 columns in d2
>>>#[1] 10
>>>
>>>
>>>#2nd problem:
>>>You are splitting using d
>>>
>>>###############Your code
>>>
>>>library(zoo)
>>>lst1<- split(d,list(d$m1,d$n1)) # should split byd2, because `d` doesn't have Qm or Qn columns
>>>d2<-do.call(rbind,lapply(lst1[lapply(lst1,nrow)!=0],function(x){
>>>x[,13:18]<-NA; #### this code was created for another dataset which obviously had 12 columns
>>>x[,13:14][x$Qm<=c11,]<-cumsum(x[,11:12][x$Qm<=c11,]); #### here your term1_p0 and term1_p1 are columns 7 and 8.
>>>
>>>x[,15:16][x$Qn<=c12,]<-cumsum(x[,11:12][x$Qn<=c12,]);
>>>x[,17:18]<-cumsum(x[,11:12]);
>>>colnames(x)[13:18]<- c("cterm1_P0L","cterm1_P1L","cterm1_P0H","cterm1_P1H","sumTerm1_p0","sumTerm1_p1");
>>>x1<-na.locf(x);
>>>x1[,13:18][is.na(x1[,13:18])]<-0;
>>>x1}
>>>))
>>>##########################################
>>>
>>>
>>>#corrected codes:
>>>
>>>lst1<- split(d2,list(d2$m1,d2$n1))
>>>
>>>dNew<-do.call(rbind,lapply(lst1[lapply(lst1,nrow)!=0],function(x){
>>>x[,11:16]<-NA;
>>>x[,11:12][x$Qm<=c11,]<-cumsum(x[,7:8][x$Qm<=c11,]);
>>>x[,13:14][x$Qn<=c12,]<-cumsum(x[,7:8][x$Qn<=c12,]);
>>>x[,15:16]<-cumsum(x[,7:8]);
>>>colnames(x)[11:16]<- c("cterm1_P0L","cterm1_P1L","cterm1_P0H","cterm1_P1H","sumTerm1_p0","sumTerm1_p1");
>>>x1<-na.locf(x);
>>>x1[,11:16][is.na(x1[,11:16])]<-0;
>>>x1}
>>>))
>>> row.names(dNew)<- 1:nrow(dNew)
>>> head(dNew,3)
>>># m1 n1 x1 y1 p11 p12 term1_p0 term1_p1 Qm Qn cterm1_P0L cterm1_P1L
>>>#1 2 2 0 0 0 0.0 0.81450625 0.31640625 1.000 1.000 0 0
>>>#2 2 2 0 1 0 0.5 0.08573750 0.21093750 0.666 0.666 0 0
>>>#3 2 2 0 2 0 1.0 0.00225625 0.03515625 0.500 0.500 0 0
>>># cterm1_P0H cterm1_P1H sumTerm1_p0 sumTerm1_p1
>>>#1 0 0 0.8145062 0.3164062
>>>#2 0 0 0.9002438 0.5273438
>>>#3 0 0 0.9025000 0.5625000
>>>
>>>
>>>A.K.
>>>
>>>
>>>________________________________
>>>
>>>From: Joanna Zhang <zjoanna2013 at gmail.com>
>>>To: arun <smartpink111 at yahoo.com>
>>>Sent: Friday, March 1, 2013 11:40 AM
>>>
>>>Subject: Re: [R] cumulative sum by group and under some criteria
>>>
>>>
>>>Hi, why there is an error when I run the cumulative sum code below?
>>>
>>>Error in `[<-.data.frame`(`*tmp*`, , 16:21, value = NA) :
>>> new columns would leave holes after existing columns
>>>
>>>
>>>maxN<-9
>>>c11<-0.4
>>>c12<-0.4
>>>c1<-0.5
>>>c2<-0.5
>>>p0L<-0.05
>>>p0H<-0.05
>>>p1L<-0.25
>>>p1H<-0.25
>>>
>>>d <- data.frame ()
>>>for ( m1 in 2: (maxN-6)) {
>>> for (n1 in 2: (maxN-m1-4)){
>>> for (x1 in 0: m1) {
>>> for (y1 in 0: n1) {
>>> p11<- (x1/m1)
>>> p12<- (y1/n1)
>>>
>>> term1_p0 = dbinom(x1,m1, p0L, log=FALSE)* dbinom(y1,n1,p0H, log=FALSE)
>>> term1_p1 = dbinom(x1,m1, p1L, log=FALSE)* dbinom(y1,n1,p1H, log=FALSE)
>>>
>>> d<-rbind(d, c(m1,n1,x1,y1,p11,p12,term1_p0,term1_p1))
>>>}}
>>>}}
>>>colnames(d)<-c("m1","n1","x1","y1","p11","p12","term1_p0","term1_p1")
>>>d
>>>tail(d)
>>>set.seed(8)
>>>d1<-do.call(rbind,lapply(seq_len(nrow(d)),function(i){
>>>Pm<- rbeta(1000,0.2+d[i,"x1"],0.8+d[i,"m1"]-d[i,"x1"]);
>>>Pn<- rbeta(1000,0.2+d[i,"y1"],0.8+d[i,"n1"]-d[i,"y1"]);
>>>Fm<- ecdf(Pm);
>>>Fn<- ecdf(Pn);
>>>Fmm<- Fm(d[i,"p11"]);
>>>Fnn<- Fn(d[i,"p12"]);
>>>R<- (Fmm+Fnn)/2;
>>>Fmm_f<- max(R, Fmm);
>>>Fnn_f<- min(R, Fnn);
>>>Qm<- 1-Fmm_f;
>>>Qn<- 1-Fnn_f;
>>>data.frame(Qm,Qn)}))
>>>d2<-cbind(d,d1)
>>>d2
>>>
>>>library(zoo)
>>>lst1<- split(d,list(d$m1,d$n1))
>>>d2<-do.call(rbind,lapply(lst1[lapply(lst1,nrow)!=0],function(x){
>>>x[,13:18]<-NA;
>>>x[,13:14][x$Qm<=c11,]<-cumsum(x[,11:12][x$Qm<=c11,]);
>>>x[,15:16][x$Qn<=c12,]<-cumsum(x[,11:12][x$Qn<=c12,]);
>>>x[,17:18]<-cumsum(x[,11:12]);
>>>colnames(x)[13:18]<- c("cterm1_P0L","cterm1_P1L","cterm1_P0H","cterm1_P1H","sumTerm1_p0","sumTerm1_p1");
>>>x1<-na.locf(x);
>>>x1[,13:18][is.na(x1[,13:18])]<-0;
>>>x1}
>>>))
>>>
>>>
>>>
>>>
>>>On Tue, Feb 26, 2013 at 8:56 PM, arun <smartpink111 at yahoo.com> wrote:
>>>
>>>??
>>>>
>>>>
>>>>
>>>>________________________________
>>>> From: Joanna Zhang <zjoanna2013 at gmail.com>
>>>>To: arun <smartpink111 at 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 <Zjoanna2013 at gmail.com>
>>>>>To: r-help at 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+s789695n4659514h45 at 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.
>>>>>> >>>> >>>>
>>>>>> >>>> >>>> ------------------------------
>>>>>> >>>> >>>> If you reply to this email, your message will be added to the
>>>>>> >>>> discussion
>>>>>> >>>> >>>> below:
>>>>>> >>>> >>>>
>>>>>> >>>> >>>>
>>>>>> >>>>
>>>>>> http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4657196.html
>>>>>> >>>> >>>> To unsubscribe from cumulative sum by group and under some
>>>>>> criteria,
>>>>>> >>>> click
>>>>>> >>>> >>>> here<
>>>>>> >>>>
>>>>>> >>>> >>>> .
>>>>>> >>>> >>>> NAML<
>>>>>> >>>>
>>>>>> http://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=macro_viewer&id=instant_html%21nabble%3Aemail.naml&base=nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.view.web.template.NodeNamespace&breadcrumbs=notify_subscribers%21nabble%3Aemail.naml-instant_emails%21nabble%3Aemail.naml-send_instant_email%21nabble%3Aemail.naml>
>>>>>>
>>>>>> >>>>
>>>>>> >>>> >>>>
>>>>>> >>>> >>>
>>>>>> >>>> >>>
>>>>>> >>>> >>>
>>>>>> >>>> >>>
>>>>>> >>>> >>>--
>>>>>> >>>> >>>View this message in context:
>>>>>> >>>> >>>
>>>>>> >>>>
>>>>>> http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4657315.html
>>>>>> >>>> >>>Sent from the R help mailing list archive at Nabble.com.
>>>>>> >>>> >>> [[alternative HTML version deleted]]
>>>>>> >>>> >>>
>>>>>> >>>> >>>______________________________________________
>>>>>> >>>> >>>[hidden email] <
>>>>>> http://user/SendEmail.jtp?type=node&node=4657773&i=18>mailing list
>>>>>> >>>
>>>>>> >>>> >>>https://stat.ethz.ch/mailman/listinfo/r-help
>>>>>> >>>> >>>PLEASE do read the posting guide
>>>>>> >>>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
>>>>>> <http://www.r-project.org/posting-guide.html>
>>>>>> >>>
>>>>>> >>>> >>>and provide commented, minimal, self-contained, reproducible code.
>>>>>> >>>> >>>
>>>>>> >>>> >>>
>>>>>> >>>> >>>______________________________________________
>>>>>> >>>> >>>[hidden email] <
>>>>>> http://user/SendEmail.jtp?type=node&node=4657773&i=19>mailing list
>>>>>> >>>
>>>>>> >>>> >>>https://stat.ethz.ch/mailman/listinfo/r-help
>>>>>> >>>> >>>PLEASE do read the posting guide
>>>>>> >>>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
>>>>>> <http://www.r-project.org/posting-guide.html>
>>>>>> >>>
>>>>>> >>>> >>>and provide commented, minimal, self-contained, reproducible code.
>>>>>> >>>> >>>
>>>>>> >>>> >>></quote>
>>>>>> >>>> >>>Quoted from:
>>>>>> >>>> >>>
>>>>>> >>>>
>>>>>> http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4657360.html
>>>>>> >>>> >>>
>>>>>> >>>> >>>
>>>>>> >>>> >>>______________________________________________
>>>>>> >>>> >>>[hidden email] <
>>>>>> http://user/SendEmail.jtp?type=node&node=4657773&i=20>mailing list
>>>>>> >>>
>>>>>> >>>> >>>https://stat.ethz.ch/mailman/listinfo/r-help
>>>>>> >>>> >>>PLEASE do read the posting guide
>>>>>> >>>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
>>>>>> <http://www.r-project.org/posting-guide.html>
>>>>>> >>>
>>>>>> >>>> >>>and provide commented, minimal, self-contained, reproducible code.
>>>>>> >>>> >>>
>>>>>> >>>> >>></quote>
>>>>>> >>>> >>>Quoted from:
>>>>>> >>>> >>>
>>>>>> >>>>
>>>>>> http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4657582.html
>>>>>> >>>> >>>
>>>>>> >>>> >>>
>>>>>> >>>> >>
>>>>>> >>>> >
>>>>>> >>>>
>>>>>> >>>> ______________________________________________
>>>>>> >>>> [hidden email] <http://user/SendEmail.jtp?type=node&node=4657773&i=21>mailing
>>>>>> list
>>>>>> >>>
>>>>>> >>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>>>> >>>> PLEASE do read the posting guide
>>>>>> >>>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
>>>>>> <http://www.r-project.org/posting-guide.html>
>>>>>> >>>
>>>>>> >>>> and provide commented, minimal, self-contained, reproducible code.
>>>>>> >>>>
>>>>>> >>>>
>>>>>> >>>
>>>>>> >>>> ------------------------------
>>>>>> >>>> If you reply to this email, your message will be added to the
>>>>>> >>>> discussion below:
>>>>>> >>>>
>>>>>> >>>
>>>>>> >>>>
>>>>>> http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4657773.html
>>>>>> >>>> To unsubscribe from cumulative sum by group and under some criteria,
>>>>>> click
>>>>>> >>>> here<
>>>>>>
>>>>>> >>>
>>>>>> >>>> .
>>>>>> >>>> NAML<
>>>>>> http://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=macro_viewer&id=instant_html%21nabble%3Aemail.naml&base=nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.view.web.template.NodeNamespace&breadcrumbs=notify_subscribers%21nabble%3Aemail.naml-instant_emails%21nabble%3Aemail.naml-send_instant_email%21nabble%3Aemail.naml>
>>>>>>
>>>>>> >>>>
>>>>>> >>>
>>>>>> >>>
>>>>>> >>>
>>>>>> >>>
>>>>>> >>>--
>>>>>> >>>View this message in context:
>>>>>> http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4658133.html
>>>>>> >>>
>>>>>> >>>Sent from the R help mailing list archive at Nabble.com.
>>>>>> >>> [[alternative HTML version deleted]]
>>>>>> >>>
>>>>>> >>>______________________________________________
>>>>>> >>>[hidden email] <http://user/SendEmail.jtp?type=node&node=4659514&i=11>mailing list
>>>>>
>>>>>> >>>
>>>>>> >>>https://stat.ethz.ch/mailman/listinfo/r-help
>>>>>> >>>PLEASE do read the posting guide
>>>>>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
>>>>>> >>>and provide commented, minimal, self-contained, reproducible code.
>>>>>> >>>
>>>>>> >>>
>>>>>> >>
>>>>>> >
>>>>>>
>>>>>> ______________________________________________
>>>>>> [hidden email] <http://user/SendEmail.jtp?type=node&node=4659514&i=12>mailing list
>>>>>
>>>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>>>> PLEASE do read the posting guide
>>>>>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
>>>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>>>
>>>>>>
>>>>>> ------------------------------
>>>>>> 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-tp4657074p4659514.html
>
>>>>>> To unsubscribe from cumulative sum by group and under some criteria, click
>>>>>> here<http://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=unsubscribe_by_code&node=4657074&code=WmpvYW5uYTIwMTNAZ21haWwuY29tfDQ2NTcwNzR8LTE3NTE1MDA0MzY=>
>
>>>>>
>>>>>> .
>>>>>> 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-tp4657074p4659717.html
>
>>>>>
>>>>>Sent from the R help mailing list archive at Nabble.com.
>>>>> [[alternative HTML version deleted]]
>>>>>
>>>>>______________________________________________
>>>>>R-help at r-project.org mailing list
>
>>>>>
>>>>>https://stat.ethz.ch/mailman/listinfo/r-help
>>>>>PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>
>>>>>and provide commented, minimal, self-contained, reproducible code.
>>>>>
>>>>>
>>>>
>>>>
>>>>
>>>
>>
>
More information about the R-help
mailing list