coverage: coverage

In matteobonvini/sensitivitypuc: Sensitivity Analysis via the Proportion of Unmeasured Confounding (PUC)

Description

coverage computes the frequentist coverage (in

Usage

coverage(lo, hi, truth_lo, truth_hi)

Arguments

lo	a n x nsim matrix, where n is the number of epsilon points used in evaluation and nsim is the number of simulations (generally lb) If it is a nsim-dim vector, the length is interpreted as the number of simulations of a scalar quantity.
hi	a n x nsim matrix, where n is the number of epsilon points used in evaluation and nsim is the number of simulations (generally ub) If it is a nsim-dim vector, the length is interpreted as the number of simulations of a scalar quantity.
truth_lo	a n x 1 vector containing the true values for the curve (lb) If lo is a vector, truth_lo must be scalar.
truth_hi	a n x 1 vector containing the true values for the curve (ub) If hi is a vector, truth_hi must be scalar.

Value

scalar equal to coverage (in

matteobonvini/sensitivitypuc documentation built on Dec. 9, 2020, 2:24 a.m.