Decision Theory and Bayesian Network
- Introduction to decision analysisElements of a decision problemThe role of uncertainty and complexity in decisionsOn the necessity of decision theory in management and busienss for leading companies
- -Structuring decisions and valuesFundamental and means objective in decision problem
- Getting the decision context rightIntroduction to influence diagramsInfluence diagrams and fundamental objective hierarchy
- Modeling decision problem by decision tree and its elementsInfluence diagrams and decision tress: relationship
- Cash flows, Probabilities in decision tres
- Making choices, Expected Monetary values (EMV) in decision treeRisk profiles and dominance
- Modeling uncertainty and probabilitiesUsing Extended Swanson-Megill Extended Pearson-Tukeyto assess subjective probabilities as degree of belief
- Using data in CDF empirical modellingTheoretical distributions and data modelingKolmogorov-Smirnov distance (K-S)Anderson-Darling distance (A-D)
- Utility concept, Utility curve, Expected utility and decision analysis with utility curveExponential utility function and ways to determine its parameter
- Introduction to statistical decision making, Bayesian decisionsBayesian estimatorsMinimax estimatorsRisk function
- Introduction to statistical decision making, Bayesian decisions Bayesian estimators Minimax estimators Risk function
- Local Markov property, markov blanket in BBNs
- Several real-life-like example in IE problems with BBNs
- Modeling with Logistic regression and its application