MonteCarlo_expectedValues: Monte Carlo Forward Simulation of Decision Tree

In n8thangreen/treeSimR: treeSimR

Description

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

Usage

MonteCarlo_expectedValues(osNode, n)

## Default S3 method:
MonteCarlo_expectedValues(osNode, ...)

## S3 method for class '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)

## End(Not run)

n8thangreen/treeSimR documentation built on Feb. 20, 2022, 11:54 a.m.