Uniform-model CDF for interval-censored data, at each observation

The same uniform-within-interval distribution function estimate as tda_midf's cdf, but evaluated at each observation's lower[i] rather than at every distinct breakpoint – TDA's midf1.

Usage

tda_midf1(lower, upper, dir = tempfile("tda"))

Arguments

lower, upper

numeric vectors, the same length, with lower[i] != upper[i] for every i.

dir

working directory.

Value

A numeric vector, the same length as lower, in the original (unsorted) order.

See also

Other matrix algebra: tda_mcel(), tda_mcent(), tda_mch(), tda_mcross(), tda_mdiag(), tda_mev(), tda_mevs(), tda_midf(), tda_midf2(), tda_midf3(), tda_minvs(), tda_mkmet(), tda_mkp(), tda_mmul(), tda_mnc(), tda_mnrow(), tda_mpbl(), tda_mpfit(), tda_mpinv(), tda_mpit(), tda_mple(), tda_mpz(), tda_mscal1(), tda_msqrtd(), tda_msvd(), tda_mwvec()

Examples

lo <- c(0, 1, 2, 3, 1)
up <- c(2, 3, 4, 5, 2)
# the estimated distribution function at each interval's own position
tda_midf1(lo, up)
#> [1] 0.0 0.1 0.5 0.7 0.1