Hi,
Could you please let me know to use a list in a for loop here geneset is a
loop.I am trying to match the names of the list with 1st row of the output.
result<- list()
for(i in 1:length(output)
{
result[[i]] <- geneset(which(geneset %n% output[,1]))
}
Kindly help me out
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Hi,
I guess this what your need. I assume your output is 10 by 11 matrix.
However, you still need to define your geneset function(?)
result<- list()
output<-matrix(NA, nrow=10, ncol=11)
for(i in 1:length(ncol(output)))
{
result[[i]] <- geneset(which(geneset %n% output[1,]))
}
Chunhao
Quoting Rajasekaramya <ramya.victory at gmail.com>:
>
> Hi,
>
> Could you please let me know to use a list in a for loop here geneset is a
> loop.I am trying to match the names of the list with 1st row of the output.
>
> result<- list()
> for(i in 1:length(output)
>
> {
> result[[i]] <- geneset(which(geneset %n% output[,1]))
> }
>
>
> Kindly help me out
>
> --
> View this message in context:
> http://www.nabble.com/For-loop-tp18163665p18163665.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> 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.
>
Hi
I have a specific sample coming from a gamma(alpha,theta1) distribution and then
divided into two parts first part follows a gamma(alpha,theta1) the second is
gamma(alpha,theta2) then I would like to find the mle`s for theta1 and theta2
which I found. Now I would like to simulate those estimates 500 or 1000 times.
I tried for loop but it did not work It wont do the loop the problem is that I
need to evaluate n1 which is the number of units in the first part. n1 could be
different each time. here is the code
r<-100n<-100shape<-2theta1<-exp(1)theta2<-exp(.5)
m0<- function(XX) #a function that generates the estimates{
loglik<-function(xx,alpha,theta1,theta2) -1*(
-r*lgamma(alpha)-alpha*n1*log(theta1)-alpha*(r-n1)*log(theta2)+(alpha-1)
*sum(log(Ti))+(alpha-1)*sum(log(Tj-tau+(theta2/theta1)*tau))-(1/theta1)*sum(Ti)-
(1/theta2)*sum(Tj-tau+(theta2/theta1)*tau)+(n-r)*log(1-pgamma((max(Tj)-tau+
(theta2/theta1)*tau)/theta2,alpha,1))) V<-mle2(minuslogl = loglik, start =
list(alpha= 2, theta1= 3, theta2= 2), data = list(size = 100))
Est<-coef(V)}estimates<-matrix(,)for (k in 1:2){
X<-rgamma(n,shape,scale=theta1) Xs<-sort(X) tau<-5 for
(i in 1:n) { if (tau-Xs[i]>0) n1=i } n1
X1<-Xs[1:n1] Ti<-X1 u=n1+1 X2<-Xs[u:n]
X3<-X2*theta2/theta1 Tj<-X3+tau-tau*theta2/theta1
c1<-matrix(Ti,ncol=1) c2<-matrix(Tj,ncol=1)
cc<-data.frame(rbind(c1,c2))[,1] cc
# the special sample that I need to find the mle`s for estimates<-
as.data.frame(t(m0(cc))) }estimates
Thanks in advance
Laila
_________________________________________________________________
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HiI have a specific sample coming from a gamma(alpha,theta1) distribution and
then divided into two parts first part follows a gamma(alpha,theta1) the second
is gamma(alpha,theta2) then I would like to find the mle`s for theta1 and theta2
which I found. Now I would like to simulate those estimates 500 or 1000 times.I
tried for loop but it did not work It wont do the loop the problem is that I
need to evaluate n1 which is the number of units in the first part. n1 could be
different each time. here is the code
r<-100n<-100shape<-2theta1<-exp(1)theta2<-exp(.5)m0<-
function(XX) #a function that generates the estimates{
loglik<-function(xx,alpha,theta1,theta2) -1*(
-r*lgamma(alpha)-alpha*n1*log(theta1)-alpha*(r-n1)*log(theta2)+(alpha-1)
*sum(log(Ti))+(alpha-1)*sum(log(Tj-tau+(theta2/theta1)*tau))-(1/theta1)*sum(Ti)-
(1/theta2)*sum(Tj-tau+(theta2/theta1)*tau)+(n-r)*log(1-pgamma((max(Tj)-tau+
(theta2/theta1)*tau)/theta2,alpha,1))) V<-mle2(minuslogl = loglik, start =
list(alpha= 2, theta1= 3, theta2= 2), data = list(size = 100))
Est<-coef(V)}estimates<-matrix(,)for (k in 1:2){
X<-rgamma(n,shape,scale=theta1) Xs<-sort(X) tau<-5 for
(i in 1:n) { if (tau-Xs[i]>0) n1=i } n1
X1<-Xs[1:n1] Ti<-X1 u=n1+1 X2<-Xs[u:n]
X3<-X2*theta2/theta1 Tj<-X3+tau-tau*theta2/theta1
c1<-matrix(Ti,ncol=1) c2<-matrix(Tj,ncol=1)
cc<-data.frame(rbind(c1,c2))[,1] cc
# the special sample that I need to find the mle`s for estimates<-
as.data.frame(t(m0(cc))) }estimates
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