Interval censoring only says the event happened somewhere in
(L, R]. The likelihood cannot distinguish points inside an
interval, so all mass sits on the innermost intervals and the NPMLE is
a discrete distribution on those. The self-consistency equation is an
EM run for a fixed number of sweeps, so the arms cannot stop apart.
Details
Formula: with alpha_ij = 1 when region j lies inside
observation i, iterate
p_j = (1/n) sum_i alpha_ij p_j / sum_k alpha_ik p_k.
Examples
V <- c(1, 2, 3, 4, 5, 6, 7, 8)
Ssintc(V, V)
#> $estimate
#> [1] 5
#>
#> $p
#> [1] 0.1428571 0.1428571 0.1428571 0.1428571 0.1428571 0.1428571 0.1428571
#>
#> $surv
#> [1] 0.8571429 0.7142857 0.5714286 0.4285714 0.2857143 0.1428571 0.0000000
#>
#> $q
#> [1] 1 2 3 4 5 6 7
#>
#> $r
#> [1] 2 3 4 5 6 7 8
#>
#> $n
#> [1] 8
#>
#> $m
#> [1] 7
#>
#> $method
#> [1] "Turnbull NPMLE, interval censoring"
#>
#> attr(,"class")
#> [1] "morie_rich_result" "list"
