similar to: Estimate hazard function from right-censored data only

Dear R users, I am trying to use "muhaz" and "plot.muhaz" functions in "muhaz" package to estimate and plot hazard funciton. However function "muhaz" always gives error message "Error in Surv(times, delta) : object "times" not found". I could not even run their sample codes in the user's manual as follows: data(ovarian)

Hello, Is it possible to create confidence intervals for hazard rates? ?I'm creating two muhaz objects:? haz1 <- muhaz(NumDaysCustomer[cRV=="true"],status[cRV=="true"]) haz2 <- muhaz(NumDaysCustomer[cRV=="false"],status[cRV=="false"]) and plotting them. ? There are many, many more observations in the cohort cRV=="false" than

Hello. ?I am hoping someone will be willing to help me understand something about hazard plots created with muhaz(...). ?I have some background in statistics (minor in grad school), but I haven't been able to figure one thing about hazard plots. ?I am using hazard plots to track customer cancellations. ?I figure I can treat a cancellation as a "death", and if someone is still a

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

Hello, If all I have access to is an empirically calculated hazard function, is it possible to compute an approximate value for the mean lifetime? I know that if the hazard function is essentially constant, the mean lifetime is 1/hazard rate. ?But if I'm confident that the empirical hazard function is not constant, I'm not sure how to go about calculating an estimate of mean lifetime.

Dear all, I'm trying to remove some text after the period (a decimal point) in the data frame 'hi', below. This is one step in formatting a table. So I would like e.g. "2.0" to become "2" and "5.3" to be "5.3", where the variable digordered contains the number of digits after the decimal that I would like to display, in the same order in which

Hello, I have the following problem. I am running simulations on possible states of a set of agents (1=employed, 0=unemployed). I store these simulated time series in a matrix like the following, where rows indicates time periods, columns the number of agents (4 agents and 8 periods in this case): Atr=[ 1 1 1 1 1 1 0 1 1 1 0 1 1 1 0 1 0 1 0 1 0

Hey all, first time poster here. I'm new to R and working on my first real programming and forecasting asignment. I'm using unemployment data from 1948-2012. I successfully completed part a and the linear fit for part b, but i am really struggling fitting a polynomial with a power greater than 2 to my forecast. I'll upload my R code at the bottom. Any help is very much appreciated!

Dear all, I am using Windows and R 2.9.2 for my analyses. I have a large dataset and I am particularly interested in looking at time to an event for a continuous variable. I would like to produce a plot of log(relative risk) or relative risk (also known as hazard ratio) against the continuous variable. I have spent a long time looking for advice on how to do this but my search has proved

Hello dear R help group, I have the following setup to analyse: We have about 150 subjects, and for each subject we performed a pair of tests (under different conditions) 18 times. The 18 different conditions of the test are complementary, in such a way so that if we where to average over the tests (for each subject), we would get no correlation between the tests (between subjects). What we wish

Dear colleagues, I have the following dataset. It is modelled on the data included in Box-Seteffenheiser and Jones "Event History Modelling" Using the following code, I try to find the baseline hazard function haz_1<-muhaz(bpa$time, bpa$censored, subset=(bpa$year=="2010" | bpa$ban=="1"), min.time=1, max.time=3) I think I'm doing everything right, but what I

Dear maintainers and R-devel, Several orphaned CRAN packages are about to be archived due to outstanding QC problems, but have CRAN and BioC packages depending on them which would be broken by the archival (and hence need archiving alongside). Therefore we are looking for new maintainers taking over maintainership for one or more of the following packages: R2HTML SemiPar cghseg hexbin lgtdl

Dear r-devel list members, On a couple of occasions I've encountered the issue illustrated by the following examples: --------- snip ----------- > mod.1 <- lm(Employed ~ GNP.deflator + GNP + Unemployed + + Armed.Forces + Population + Year, data=longley) > mod.2 <- update(mod.1, . ~ . - Year + Year) > all.equal(mod.1, mod.2) [1] TRUE > > f <-

[This question is hopefully straight-forward, but difficult to provide reproducible code.] I'm doing a multivariate bootstrap, using boot::boot(), where the output of the basic computation is a k x p matrix of coefficients, representing a tuning constant x variable, as shown in the $t0 component from my run, giving a 3 x 6 matrix > lboot$t0 GNP Unemployed Armed.Forces

Dear R List, I have a dataset with the following structure: """personal_id, p_0, p_1, p_2, .... , p_36, p_37 1, NA, 1, 4, .... , 1, NA 2, NA, NA, NA, .... , 4, NA . . . 6020, NA, 3, 3, ...., NA, NA 6021, NA, 2, 2, ...., 4, NA """ I used some made-up data. It is just meant to show the structure of the dataset. The variables of interest are p_0, ... p_37.

In Germany the Unemployment Agency uses a sectioning of the german map that is different from the usual Administrative Boundaries. Some demographic data are available in Administrative Boundaries only, some in Unemployment Boundaries only. I would like to generate estimates in one boundary system of data availabe in the other boundary system, and would appreciate advice concerning the following

I'm trying to make a set of contour plots of bivariate kernel density estimates, showing three such plots overlaid, similar to this plot http://euclid.psych.yorku.ca/SCS/Private/Test/ridge-boot2.pdf except that I would like to have the contours *filled* (using transparent colors). To make this reproducible, I've saved the results of KernSmooth::bkde2D() in the following file:

Hi, I am working on fitting a proportional hazard model to predict the probability of default for mortgage loans. I have a question regarding survfit function. My historical data set is a pool of loans with monthly observed default status for the next 24 months. The data is left truncated (delayed entry to observation window after the loan is opened) and right censored. I would like to

Hello, I have posted this mail a few days ago but I did it wrong, I hope is right now: I have the following doubts related with lm.ridge, from MASS package. To show the problem using the Longley example, I have the following doubts: First: I think coefficients from lm(Employed~.,data=longley) should be equal coefficients from lm.ridge(Employed~.,data=longley, lambda=0) why it does not happen?

Dear all I'm familiarising myself with Ridge Regressions in R and the following is bugging me: How does one get p-values for the coefficients obtained from MASS::lm.ridge() output (for a given lambda)? Consider the example below (adapted from PRA [1]): > require(MASS) > data(longley) > gr <- lm.ridge(Employed ~ .,longley,lambda = seq(0,0.1,0.001)) > plot(gr) > select(gr)