dexisensitivity1.0.2 package

'DEXi' Decision Tree Analysis and Visualization

aov_tree

Dual Order AOV on a Decision Tree

compare_scenarios

Compare Scenarios Using a Radial Plot

create_list_synoptique

Create a List of Synoptic Plots Based on Different Options

create_options

Generate Random Options Matrix for a Given Tree

create_sub_tree

Create a Subtree Starting from a Specific Node

create_synoptique

Create a Synoptic Plot from a Given Tree Structure

create_tree

Tree Construction from DEXi's XML Output

describe-Tree-method

Describe Method for Tree Class Objects

describe

Generic Describe Function for Objects

dexisensitivity-package

dexisensitivity: 'DEXi' Decision Tree Analysis and Visualization

estimate_aov_time

Execution Time Estimation for Factorial Simulations

estimate_mc_time

Estimates Execution Time for Monte Carlo Simulations

evaluate_scenario

Evaluate Node Values in a Tree

evaluate_scenarios

Evaluate Multiple Scenarios for a Given Tree

get_sensitivity_index

Compute Sensitivity Index for Decision Tree

load_options

Load Options Table from a File

monte_carlo

Monte Carlo Simulation on a Decision Tree

Node-class

Node Class Definition

oat

OFAT Sensitivity Analysis

plot_sensitivity_index

Show Sensitivity Index (SI)

print-Node-method

Print Method for Node Class Object

print-Tree-method

Print Method for Tree Class Objects

save_options

Save Options Table

save_scenarios

Save Evaluation Results of Scenarios to a File

show_mc_results

Visualization of Monte Carlo Simulation Results

show_oat_results

Visualize OFAT Sensitivity Analysis Outcomes

show_scenario

Plot a Bar Chart for a Single Scenario

show-Tree-method

Show Method for Tree Class Objects

si_dexi

Compute Sensitivity Index (SI) for Decision Tree

Tree-class

Tree Class Definition

visualize_aov

Visualize AOV Outcomes

Provides a versatile toolkit for analyzing and visualizing 'DEXi' (Decision EXpert for education) decision trees, facilitating multi-criteria decision analysis directly within R. Users can read .dxi files, manipulate decision trees, and evaluate various scenarios. It supports sensitivity analysis through Monte Carlo simulations, one-at-a-time approaches, and variance-based methods, helping to discern the impact of input variations. Additionally, it includes functionalities for generating sampling plans and an array of visualization options for decision trees and analysis results. A distinctive feature is the synoptic table plot, aiding in the efficient comparison of scenarios. Whether for in-depth decision modeling or sensitivity analysis, this package stands as a comprehensive solution. Definition of sensitivity analyses available in Carpani, Bergez and Monod (2012) <doi:10.1016/j.envsoft.2011.10.002> and detailed description of the package soon available in Alaphilippe et al. (2025) <doi:10.1016/j.simpa.2024.100729>.

  • Maintainer: Nicolas Cavan
  • License: GPL (>= 2)
  • Last published: 2025-09-08