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...o check it for me as the output that i got is not what i desired...thanks.. data<-rnorm(20,0,1) dim(data)<-c(5,4) is.matrix(data) data a<-function(x) { for(i in 1:nrow(x)) { for(j in 1:ncol(x)) { med<-median(x[,j])? mean<-mean(x[i,]) print(c(med=med,mean=mean)) } } } a(data)? Chris Guure Researcher Institute for Mathematical Research UPM

...q<-replicate(1000,x) the right way to do simulation. thank you. x<-rweibull(100,0.8,1.5) q<-replicate(1000,x) z<-function(p){ beta<-p[1] eta<-p[2] log1<-(n*log(beta)-n*beta*log(eta)+(beta-1)*sum(log(x))-sum((x/eta)^beta)) return(-log1) } zz<-optim(c(0.5,0.5),z) zz Chris Guure postgraduate researcher/tutor Institute for Mathematical Research Universiti Putra Malaysia  [[alternative HTML version deleted]]

Hello, ?can i implement this as 10% censored data where t gives me failure and x censored. Thank you p=2;b=120 n=50 set.seed(132); r<-sample(1:50,45) t<-rweibull(r,shape=p,scale=b) t set.seed(123);? cens <- sample(1:50, 5)? x<-runif(cens,shape=p,scale=b)? x Chris Guure Researcher, Institute for Mathematical Research UPM

...ution. Below is the code for it. I will need to know whether what i have done is correct and if not, can i have any suggestion to improve it? Thank you ?p=2;b=120 n=50 r=45 t<-rweibull(r,shape=p,scale=b) meantrue<-gamma(1+(1/p))*b meantrue cen<- runif(n-r,min=0,max=meantrue) cen Chris Guure Researcher, Institute for Mathematical Research UPM

...n,1,0) z<-function(data,p){? beta<-p[1] eta<-p[2] log1<-(n*cen*log(p[1])-n*cen*(p[1])*log(p[2])+cen*(p[1]-1)*sum(log(t))-n*sum((t/(p[2]))^(p[1]))) return(-log1) } start <-c(0.5,0.5) zz<-optim(start,fn=z,data=q,hessian=T) m1<-zz$par[2] p<-zz$par[1] } m1 p Thank you Chris Guure Researcher Institute for Mathematical Research UPM

...scale<-p[2] > log1<-(r*log(p[1])-r*(p[1])*log(p[2])+(p[1]-1)*sum(log(t))-sum((t/(p[2]))^(p[1]) > )-((n-r)*(sum(cen)/(p[2]))^(p[1]))) > return(-log1) > } > > start <- c(1,1) > zz<-optim(start,fn=z,hessian=T) > zz > > Thanks in anticipation > > Chris Guure > Researcher > Institute for Mathematical Research > UPM

...x[1:b]<-(m[,2]) v<-x[1:b] q<-cbind(u,v) h<-c(t,q) z<-function(data ){? rate<-p[2] log1<--(n/log(p[2]))-sum(t/(p[2]))+sum(log(exp(-(u/(p[2])))-exp(-(v/(p[2]))))) return(-log1) } } start <- c(1,1) zz<-optim(start,fn=z,data=h,hessian=T) m1<-zz$par[2] thank you chris b guure researcher institute for mathematical research? upm??