search for: uncens

...2,5,6,5,7,3,4,5,2,4,1,5,6,7,6,5,2,5,6,5,7,3,4,5, 6,5,7,8,5,6,8,6,5,6,8,6,5,8,6,9,6,5,7,8,5,6,8,6,5,6,8,6,5,8,6,9),2) treat<-rep(c(0,1),each=64) covar<- rep(c(1,3,2,5,6,4,7,8,9,6,4,3,4,3,2,1,4,3,5,4,6,3,4,5,6,4,6,3,6,7,4,5,3,4,5,6,4,6,6,4,7,6,5,7,5,4,3,2,8,6,4,9,7,9,5,4,6,8,6,4,6,2,5,8),2) uncens<- rep(c(0,1,0,0,0,1,0,0,1,1,1,1,0,1,1,0,0,1,0,0,0,1,0,0,1,1,1,1,0,1,1,0 ,0,1,1,0,0,1,0,0,1,0,1,0,0,0,1,1,0,1,1,0,0,1,0,0,1,0,1,0,0,0,1,1),2) centers<- rep(rep(1:32, 2),2) data1<-list(y, treat, covar, uncens, centers) names(data1)<- c("y", "treat", "covar"...

Hi Arun, thank-you very much! The 2nd option worked perfectly. That was what I wanted. Now, I have another question. I am using the R packages dataRetrieval and EGRET from https://github.com/USGS-CIDA/WRTDS. I have 2 objects Daily and Sample that have the naming convention (Names = "21NC02WQ.C1000000" or whatevver the list of site names happens to be) that I need to have after running

...#X2 Covariate=Type of treatment(1=chemo,0=radio) # L1<-length(cens) #number of censored# for (j in 1:L1) { if ((cens[j]==1)&(curd[j]==0)) {(cen[j]=1)&(cur[j]=1)} else {(cen[j]=cens[j])&(cur[j]=curd[j])} } Now, the following is my data: ####### My Data only with uncensored and right censored #################### data=data.frame(Ti=dat1$time,Censored=cen) #################### Estimation using Surv pakage ############################ library(survival) survreg(Surv(Ti, Censored)~1, data=data, dist="lognormal") ########### Seperating the data for simply u...

Hi, I am trying to get the maximum likelihood estimator for lognormal distribution with censored data;when we have left, interval and right censord. I built my code in R, by writing the deriving of log likelihood function and using newton raphson method but my estimators were too high " overestimation", where the values exceed the 1000 in some runing of my code. is there any one can