similar to: parameter estimation -- Censored mean to real mean

Hi all, Does anybody have the experience of using optim to estimate variables with integral forms? here the code: trun.mean<- function(x) # t is the threshold { mu=x[1]; sigma=x[2]; t=x[3]; f <- function(x) (1/(sigma*sqrt(2*pi)))*exp(-(x-mu)^2/(2*sigma^2)); pdf.fun <- function(x) x*f(x); integrate(f,thre,upper=Inf)$value/integrate(pdf.fun,thre,upper=Inf)$value ; } when I

Dear R Help, I'd like to be able to use gamlss to generate distributions that are both truncated and have censoring. It doesn't look as though it is possible to do this at the moment: > gen.trun(par=c(0),family="NO",name="tr",type="left") A truncated family of distributions from NO has been generated and saved under the names: dNOtr pNOtr qNOtr rNOtr

Hi, I need to get mean and variance of right censored data. How can I do that? I have a vector of values (called a) and vector of booleans (whether value is censored) (called b). What to do with this? Sorry, I'm R beginner. Thank you! Pete

Hello, I'm trying to calculate the Maximum likelihood estimators for a dataset which contains censored data. I started by using the function "nlm", but isn't there a separate method for doing this for e.g. the "weibull" and the "log-normal" distribution? Thanks, Olivia [[alternative HTML version deleted]]

I am aware of the nice R package "logspline", which does smooth density estimation from interval-censored data (that is, values that are known to lie in a specified interval rather than known exactly). Function logspline.fit uses a maximum penalized likelihood method, with the penalty related to the number of knots used in a cubic regression-spline fit. I need to be able to do some

Hi List, I was not able to make this work. I know it is a simple one, sorry to bother. Give me some hints pls. Thanks! Jen if(length(real.d)>=30 && length(real.b)>=30 && beta1*beta2*theta1*theta2>0 ) { r <- 1; corr <- 1; } real.d and real.b are two vectors, beta1,beta2,theta1,and theta2 are constants. The error occurred like this: Error in if

Hello, I have been googling for 2 days and I cannot find the answer in previous posts. I have a set of d-dimensional data elements (d=11 .. 14), each data point can be censored at different values both Lower-limit and upper limit. N = 2000 sets of vectors of D=11 data points per vector. Each of the N*D points can have different upper and lower limits. I "simply" want to fit a

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

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Dan Phillips wrote: > Charles Steinkuehler wrote: >> Dan Phillips wrote: >> >> What we are left with is a requirement in abcde to overcome this and >> >> until then we have the manual method. Have you any thoughts on the best >> >> way to overcome this problem apart from the hacked toc3cue (do you have

Can anybody give me a neat example of interval censored data analysis codes in R? Given that suvreg(Surv(c(1,1,NA,3),c(2,NA,2,3),type="interval2")~1) works why does survreg(Surv(data[,1],data[,2],type="interval2")~1) not work where data is : T.1 T.2 Status 1 0.0000000 0.62873036 1 2 0.0000000 2.07039068 1 3 0.0000000

Dear R users, I tried to analysis the hazard function of some data by coxph function in survival package. The type of the data include "left-censored", "right-censored", "both right-censored and left-censored" (btw, does this has a technical term?), and "complete" ones. I noticed that event (one parameter in "Surv()") might be an indicator for the

Hi all! I have two survival data sets looking at similar effects in different settings. One data set is only right censored, but the other is interval censored. In the right censored data set, there is an effect of one factor that causes very different shapes in survival curves (and non-proportional hazards) and I'd really like to say that the same factor has a similar effect in the other

One set of data has censored (less-than detection limits) water chemistry concentrations for 80-100% of all observations. My initial trial-and-error attempts to apply the cenboxplot() method suggests that it has an upper limit to the percentage of censored observations. I do not see this limit in Dennis Helsel's second edition. Has anyone experience plotting censored data and can provide

I need to give a quick description of Tobit Regression (TR), including how it differs from ordinary least squares (OLS). I am an ecologist who knows just enough about remote sensing and statistics to be dangerous in both. Now I have found myself doing a remote sensing project where I have used TR: survreg(Surv()). As far as I can tell, no form of Censored Regression has been used in analyzing

I start by doing a simple gaussian tobit by MLE: x1 <- runif(1000) # E() = 0.5 x2 <- runif(1000)*2 # E() = 1 x3 <- runif(1000)*4 # E() = 2 ystar <- -7 + 4*x1 + 5*x2 + rnorm(1000) # is mean 0 y <- ystar censored <- ystar <= 0 y[censored] <- 0 library(AER) m <- tobit(y ~ x1 + x2, left=0, data=D) summary(m) Which gives: Call:

dear R-users, I have to model counts where all counts above some threshold have been censored. In the same dataset I have too many zeroes for a Poisson or even a negative binomial distribution to make sense, so I would need a zero-inflated-censored negative binomial family for use in glmer (or glmmADMB?). That seems not to exist. my question is : how could I add a custom-built family of

Dear list, I would like to plot the empirical cumulative distribution of the time needed by a treatment to attain a certain goal. A number of experiments is run with a strict time limit. In some experiments the goal is attained before the time limit, in other experiments time expires before the goal is attained. The situation is very similar to survivial analysis with censored data. I tryed

Hi All, I'm trying to figure out the cumulative incidence curve in R in some limited time. I found in package "cmprsk", the command "plot.cuminc" can get this curve. But I noticed that there is no mark for the censored time there, comparing with the KM curve by "plot.survfit". Here are my codes (attached is the data): ----------------

First let me admit that I am no statistician... rather, an ecologist with just enough statistical knowledge to be dangerous. I've got a dataset with percent ground cover values for species and other entities. The data are left censored at zero, in that percent ground cover cannot be negative. (My data rarely reach 100% cover so I haven't bothered with adding a right censoring at 100).

Dear all, I want to compute the NPMLE for interval censored data using the EMICM function in Icens package, but I didn't find much detailed instructions on how to use this. I couldn't even figure out how to specify the status of right censored, interval censored, observed. (probably due to my level of understanding.) Does anyone have experience on using this and could you please help me?