Implemented Features
- A detail report in the recommendation panel is shown when no decision can be made.
- A new Event Distribution Chart is shown in the Risk Profile.
- If no winner can be selected based on the selected decision criteruia, the explanation is displayed in the Result Panel.
- User can change the unit of utility, no more hard coded "Utils", rather use any unit you want.
- A dedicated Analytic Hierarchy Process modeling tool is introduced.
- In AHP, now, UNLIMITED level of SUB-CRITERIA can be modeled for each Criteria
- In AHP, a graphical tree is displayed for Goal, Criteria and Sub-Criteria
- The pairwise comparison User interface ticks into only numbers from 1 to 9, which makes the calculation more accurate
- In AHP, a new MATRIX view is available so that the user can see the entire matrix table of pairwise comparison, and interacts with the matrix.
- Probability Tree analysis using Decision Tree without creating any criteria or payoff.
- Panning: Hold the left mouse button down and pan the Decision Tree Diagram to navigate easily.
- In decision tree. show a rejection symbol on the action node which is rejected.
- Diagram node can be deselected using ESC key or context menu.
- Entropy can be displayed in both SHANON (Bits) and Nat, also, Entropy can be calculated for Payoff variation or Event variation.
- Cost-Effectiveness Improvement: Sensitivity Analysis is performed for inidivusal variables in QALY or DALY.
- Cost-Effectiveness Improvement: User can choose a DALY formula to use.
- Cost-Effectiveness Improvement: User can chose the QALY formula to use.
- Cost-Effectiveness Improvement: Improved the Cost Criterion.
- Added Criteria Weighted Attribute Stack Charts and Polar Charts so that user can see which Criterion is affecting the decision in what degree.
- Implemented Mixed-Mode High DPI scaling feature so the app will scale smoothly when moved from various monitors with different DPI.
- Updated to .net 4.8, so performance is highly improved.
- Integrated Markov Decision Process Directly into the Decision Tree
- Integrated Bayesian Network and Bayesian Inference