simulate_bounds: Simulate bounds

Description Usage Arguments Value Examples

View source: R/process-optimizer.R

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

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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

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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)

causaloptim documentation built on Dec. 11, 2021, 9:56 a.m.