Monte Carlo Forward Simulation of Decision Tree

Source: R/calc_expectedValues.R

Results are returned for the nodes labelled logical in decision tree. Require at least one logical node.

MonteCarlo_expectedValues(osNode, n)

# S3 method for default
MonteCarlo_expectedValues(osNode, ...)

# S3 method for costeffectiveness_tree
MonteCarlo_expectedValues(osNode,
  n = 100)

Arguments

osNode

A data.tree object with class costeffectiveness_tree
n

Number of simulations

Value

list containing array of n sets of expected values and sampled nodes full names

See also

calc_expectedValues

Examples

# NOT RUN {
## read-in decision tree
osNode <- costeffectiveness_tree(yaml_tree = "raw data/LTBI_dtree-cost-distns.yaml")
print(osNode, "type", "p", "distn", "mean", "sd")

## calculate a single realisation expected values
osNode <- calc_expectedValues(osNode)
print(osNode, "type", "p", "distn", "mean", "sd", "payoff")

## calculate multiple realisation for specific nodes
MonteCarlo_expectedValues(osNode, n=100)
# }