HiI am using the boot function in boot package. I am facing a problem in 
getting the values of bias and st.error in the output. 
r<-36n<-40shape<-2theta11<-exp(1) # (=2.718282)theta21<-exp(.5) #( 
=1.648721)m0<- function(Ti,Tj)  #a function that generates the MLestimates{   
loglik<-function(ti,tj,alpha,theta1,theta2){       -1*( 
log(n)-log(n1)-log(r-n1)-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= 11,theta2= 3), data = list(size = 20))   
Est<-coef(V)}sample1<-function(n,r,tau,shape,theta1,theta2) #the function that 
generate the sample{         U<-runif(n)          Us<-sort(U)          F1tau<- 
pgamma((tau/theta1),shape,1)          n1<-sum(Us<F1tau)          X1<- Us[1:n1]  
      !
   X2<- theta1*qgamma(Us[1:n1],shape,1)          Ti<- X2          w=n1+1        
  V<- Us[w:r]             V1<-theta2*qgamma(V,shape,1)          
Tj<-V1+tau-(theta2/theta1)*tau          c(Ti,Tj)          }  
sample1(40,36,5,2,exp(1),exp(.5))func2<- function(data,mle){                
sample1(n,length(data),tau,shape,mle[2],mle[3])          
}func1<-function(data){   loglik<-function(data,alpha,theta1,theta2){       
-1*( 
log(n)-log(n1)-log(r-n1)-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= 11,theta2= 3), data = list(size = 20))   
Est<-coef(V) }  bootobject <- boot(data=c(Ti,Tj) , statistic= func1 , 
R=1000,sim='parametric', ran.gen=func2,                    mle= m0(Ti,Tj) ) 
boot.ci(!
 bootobject, conf=.90, type= 'bca') Thank you and take care.Laila 
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