similar to: Fitting mean and covariance of Multivariate normal with censored data

Hello All If I check the package fAssets using R-3.1.1 (2014-07-10 under Windows) I don't get any notes. If I do the same using R-Devel (2014-09-17 r66626 under Windows) I get the following note: . assetsMeanCov: no visible binding for global variable 'scaleTau2' . I'll try to explain why with a minimal example. Let's have a look at the following function: assetsMeanCov

I would like to make bar plots where the bars are composed of text like this: http://www.thomaslevine.com/lowres/text_bars.png Is there a package that will help me with this? Thanks Tom

Hi: I am having problems with isolinux.cfg I am receiving several error messages. 'Missing parameter in config file' and 'Unknown keyword in config file'. Here is a copy of my Isolinux.cfg maybe sombody can help me figure it out: default ks prompt 1 timeout 60 display custom.msg F1 boot.msg F2 options.msg F3 general.msg F4 param.msg F5 rescue.msg F7 custom.msg

dear all, I would like to know whether survdiff and survReg function in the survival package work for left-truncated and right-censored data. If not, what other functions can i use to make comparison between two survival curves with LTRC data. thanks for any help given sing yee

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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

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]]

Hi, I am trying to figure out how to put tick marks for censored observations using plot.cuminc for my competing risk analysis (survfit does this automatically). I've searched online for resources but found nothing. Does anybody know how to do this? Thank you in advance for your input. KC [[alternative HTML version deleted]]

Hi just wondering if there is a package that can get the maximum likelihood or method of moments estimator for distributions with censored data? The distributions I'm interested in are: Exponential, pareto, beta, gamma and lognormal. -- View this message in context: http://www.nabble.com/MLE-for-censored-distributions-in-R-tp15022863p15022863.html Sent from the R help mailing list archive at

Dear list, I am wondering whether R allows to perform a Poisson regression on counting data which include censored observations, that is, observations of the form "2 events or more" or "less than 2 events" or even "1 or 2 events". Can anyone give me a hint whether this is already possible and how to do it? Data of the form (obstime is the observation time,

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

I am a student (and very to new to R) working on a senior design project that is attempting to determine the demand distributions for single copy newspaper draws at individual sales outlet locations. Our sales data is right-censored, because sell-outs constitute a majority of the data, and we are also testing the relevance of including covariates (weather, seasonality, economic condition, etc.).

Hi, dear R-help, I want to fit a Buckley-James censored regression without intercept. The function bj() inside the Design library have to have an intercept, I try Surv(y,d)~ 0 + x , or -1+x, or x-1, none works. Any suggestions? Is there another BJ() code out there that do not have to have an intercept? Or may be it is easier to modify the bj()? I need the estimator only, no need of var estimate

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

Hi, I am wondering how to specify interval-censored data in coxph? The example in the help page summary(coxph(Surv(start, stop, event) ~ x, data = test2)) is for counting process data, is the counting process data the same as interval-censored data? Thanks __________________________________

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

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

Hi, I want to plot non parametric estimates of the empirical hazard function for right censored data. I've tried many functions from different packages (muhaz, Design, survival, eha, event), but none of them gave me what I wanted. Am I missing something? Here's what I want. The data below is the same used by Kiefer (J. Economic Literature, 1988), which in turns use a subset of the data

Dear All, I would like to ask if it is possible to estimate a hazard function using the muhaz command when all the data is right-censored. My data has information of the number of weeks people has been unemployed but all of them are unemployed at the date of the survey, that is, I cannot observed when the individuals leave the unemployment state. I appreciate your help, Best, Monica L.

Hi List, Is there anyway to estimate the parameters with integral forms? Here is the function. The idea is to calculate the real mean from the censored mean given normal distribution. I have the function as trun.mean<- function(mu,sigma,t) # t is the threshold { f <- function(x) (1/(sigma*sqrt(2*pi)))*exp(-(x-mu)^2/(2*sigma^2)); pdf.fun <- function(x) x*f(x); mut <-