Threshold Interventions

stop_at_threshold(prob, obs, threshold)

Simulates prob until obs == threshold.

optimal_threshold_intervention(prob, [p1 = prob.p], p2, obs, threshold, duration; maxtime)

Arguments

• p1: parameters for the pre-intervention scenario. Defaults to prob.p.
• p2: parameters for the pose-intervention scenario.
• obs: The observation symbolic expression.
• threshold: The threshold for the observation.
• duration: Duration for the evaluation of intervention.

Keyword Arguments

• maxtime: Maximum optimization time. Defaults to 60.

Returns

• opt_tspan: Optimal intervention time span.
• (s1, s2, s3): Pre-intervention, intervention, post-intervention solutions.
• ret: Return code from the optimization.

optimal_parameter_intervention_for_threshold(prob, obs, threshold, cost, ps,
    lb, ub, intervention_tspan, duration; ineq_cons = nothing, maxtime=60)

Arguments

• prob: An ODEProblem.
• obs: The observation symbolic expression.
• threshold: The threshold for the observation.
• cost: the cost function for minimization, e.g. α + 20 * β.
• ps: the parameters that appear in the cost, e.g. [α, β].
• lb: the lower bounds of the parameters e.g. [-10, -5].
• ub: the upper bounds of the parameters e.g. [5, 10].
• intervention_tspan: intervention time span, e.g. (20.0, 30.0). Defaults to prob.tspan.
• duration: Duration for the evaluation of intervention. Defaults to prob.tspan[2] - prob.tspan[1].

Keyword Arguments

• maxtime: Maximum optimization time. Defaults to 60.
• ineq_cons: a vector of symbolic expressions in terms of symbolic parameters. The optimizer will enforce ineq_cons .< 0.

Returns

• opt_p: Optimal intervention parameters.
• (s1, s2, s3): Pre-intervention, intervention, post-intervention solutions.
• ret: Return code from the optimization.