Visualize the cost functions for the intervention components. This function creates a Shiny app that allows the user to adjust the coefficients of the cost functions for each intervention component and visualize the resulting total cost function and its derivative. The initial coefficients are calculated based on the unit costs, the default cost function type (linear or cubic), and the lower and upper bounds. The user can adjust the coefficients using sliders and reset them to their initial values. Each slider has a default range scaled to its coefficient's magnitude (derived from the unit costs and bounds), and the user can set a custom range for any slider using its "Range min" / "Range max" inputs. The app also displays the current coefficient vector for each component. The user can copy the final coefficient list for use in the optimization function lago_optimization().
Usage
visualize_cost(
component_names,
unit_costs,
default_cost_fxn_type,
intervention_lower_bounds,
intervention_upper_bounds
)Arguments
- component_names
A character vector of the names of the intervention components.
- unit_costs
A numeric vector of the unit costs for each intervention component.
- default_cost_fxn_type
A character string specifying the default cost function type. Must be either "linear" or "cubic".
- intervention_lower_bounds
A numeric vector of the lower bounds for each intervention component.
- intervention_upper_bounds
A numeric vector of the upper bounds for each intervention component.
Value
Invisibly, the cost-function coefficient list
(a list of numeric vectors, one per intervention component) as it stood
when the app was closed, suitable for passing to
lago_optimization(cost_list_of_vectors = ...). The same list can be
copied from within the app.
Details
When the app is closed with the "Return list to R & close" button,
the coefficient list is also assigned to lago_cost_list in the global
environment (overwriting any existing object of that name) and a message
reports this, so the list is available even when the app was launched with a
bare visualize_cost(...) call rather than cost_list <-
visualize_cost(...). Closing the browser tab instead of using the button
does not save the list.