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 Thanks in advanceLaila
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