simulate_bounds {causaloptim}

Simulate bounds

Description

Run a simple simulation based on the bounds. For each simulation, sample the set of counterfactual probabilities from a uniform distribution, translate into a multinomial distribution, and then compute the objective and the bounds in terms of the observable variables.

Usage

simulate_bounds(obj, bounds, nsim = 1000)

Arguments

obj

Object as returned by analyze_graph

bounds

Object as returned by optimize_effect

nsim

Number of simulation replicates

Value

A data frame with columns: objective, bound.lower, bound.upper

Examples

b <- graph_from_literal(X -+ Y, Ur -+ X, Ur -+ Y)
V(b)$leftside <- c(0,0,0)
V(b)$latent <- c(0,0,1)
V(b)$nvals <- c(2,2,2)
E(b)$rlconnect <- E(b)$edge.monotone <- c(0, 0, 0)
obj <- analyze_graph(b, constraints = NULL, effectt = "p{Y(X = 1) = 1} - p{Y(X = 0) = 1}")
bounds <- optimize_effect(obj)
simulate_bounds(obj, bounds, nsim = 5)