Nonparametric maximum likelihood estimation for survival data
In longevity: Statistical Methods for the Analysis of Excess Lifetimes

The longevity package includes an implementation of Turnbull's EM algorithm for the empirical distribution function for data subject to arbitrary censoring and truncation patterns.

For example, we can consider the interval censored data considered in @Lindsey.Ryan:1998. The left and right give respectively.

#| label: fig-aids
#| eval: true
#| echo: true
#| fig-cap: "Nonparametric maximum likelihood estimate of the distribution function for the AIDS data"
#| out-width: '80%'
#| fig-width: 12
#| fig-height: 8
library(longevity)
left <- c(0,15,12,17,13,0,6,0,14,12,13,12,12,0,0,0,0,3,4,1,13,0,0,6,0,2,1,0,0,2,0)
right <- c(16, rep(Inf, 4), 24, Inf, 15, rep(Inf, 5), 18, 14, 17, 15,
           Inf, Inf, 11, 19, 6, 11, Inf, 6, 12, 17, 14, 25, 11, 14)
test <- np_elife(time = left,   # left bound for time
                 time2 = right, # right bound for time
                 type = "interval2", # data are interval censored
                 event = 3) # specify interval censoring, argument recycled

plot(test)

We can also extract the equivalence classes and compare them to @Lindsey.Ryan:1998: these match the values returned in the paper. The summary statistics reported by the print method include the restricted mean, which is computed by calculating the area under the survival curve.