akritas | R Documentation |
The Akritas survival estimator is a conditional nearest-neighbours approach to the more common Kaplan-Meier estimator. Common usage includes IPCW Survival models and measures, which do not assume that censoring is independent of the covariates.
akritas(
formula = NULL,
data = NULL,
reverse = FALSE,
time_variable = "time",
status_variable = "status",
x = NULL,
y = NULL,
...
)
formula |
|
data |
|
reverse |
|
time_variable |
|
status_variable |
|
x |
|
y |
|
... |
|
This implementation uses a fit/predict interface to allow estimation on unseen data after fitting on training data. This is achieved by fitting the empirical CDF on the training data and applying this to the new data.
An object inheriting from class akritas
.
Akritas, M. G. (1994). Nearest Neighbor Estimation of a Bivariate Distribution Under Random Censoring. Ann. Statist., 22(3), 1299–1327. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1214/aos/1176325630")}
if (requireNamespaces(c("distr6", "survival"))) {
library(survival)
akritas(Surv(time, status) ~ ., data = rats[1:10, ])
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.