Survival analysis is the statistics of censored time to event data, to which standard regression and classification techniques generally do not apply, due to the uncertain group memberships of the observations.
I’m trying to fit and plot a Weibull model to a survival data. The data has just one covariate, …
r plot survival-analysis weibullArgh! I keep getting the following error when attempting to compute with my neural network: > net.compute <- …
r machine-learning artificial-intelligence neural-network survival-analysisI'm having some trouble using coxph(). I've two categorical variables: Sex and Probable Cause, that I want to use as …
r survival-analysis categorical-data cox-regressionggadjustedcurves error: Must use a vector in '[', not an object of class matrix I call rlang::last_trace() …
r survival-analysisI have the following survreg model: Call: survreg(formula = Surv(time = (ev.time), event = ev) ~ age, data = my.data, dist = "…
r plot survival-analysis weibull parametric-equationsI'm trying to use the R survival package, to produce a plot of log(-log(survival)) against log(time) (This …
r survival-analysisI'm having some trouble using coxph(). I've two categorical variables:"tecnologia" and "pais", and I want to evaluate the possible …
r survival-analysis cox-regressionI'm trying to build a neural net with the neuralnet package and I'm having some trouble with it. I've been …
r machine-learning artificial-intelligence neural-network survival-analysisI've been looking for a solution to plot survival curves using ggplot2. I've found some nice examples, but they do …
r ggplot2 survival-analysisI've created this model: model <- survfit(Surv(time,status)~c$sex) model and the output is: Call: survfit(…
r extract survival-analysis