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This thesis presents a detailed sensitivity analysis of Howard\'s policy-iteration technique used for addressing Markovian decision problems. It explores the method\'s responsiveness to random errors in transition probabilities, identifies factors affecting sensitivity, and analyzes variations across different problems. Additionally, the study involves experimental procedures utilizing perturbations to transition matrices and evaluates implications for optimal policy selection in dynamic...
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Define the parameters of the model you want to analyze.
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Identify the critical inputs that will be varied in the sensitivity analysis.
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Determine the range of values for each input to assess.
04
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Change one input parameter at a time while keeping others constant to evaluate its impact.
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A sensitivity analysis is a technique used to determine how different values of an independent variable affect a particular dependent variable under a given set of assumptions.
Entities involved in projects that require risk assessments, such as financial analysts, project managers, and companies executing regulatory compliance are often required to file a sensitivity analysis.
To fill out a sensitivity analysis, identify the key variables, determine their potential range of values, run simulations or calculations based on these ranges, and present the results, usually in tables or graphs.
The purpose of a sensitivity analysis is to assess the impact of variability in input variables on the output results, providing insights into which variables have the most influence on outcomes.
Information that must be reported includes the range of values for each variable tested, the methodology used for analysis, the results of the analysis, and any assumptions made.
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