herkkyysanalyyseihin

Herkkyysanalyysi, often translated as sensitivity analysis, is a technique used in modeling and simulation to understand how the uncertainty in the output of a model can be attributed to different sources of uncertainty in its inputs. It systematically investigates how changes in input variables affect the model's results. This is crucial for assessing the robustness and reliability of model predictions, especially when dealing with complex systems where multiple factors can influence the outcome.

The primary goal of herkkyysanalyysi is to identify which input parameters have the most significant impact on the model's output. This helps in prioritizing data collection efforts, refining model assumptions, and understanding the key drivers of the model's behavior. It can also reveal non-linear relationships and interactions between input variables that might not be apparent through simple observation.

Various methods exist for conducting herkkyysanalyysi, ranging from simple one-at-a-time (OAT) approaches, where each input variable is varied while others are held constant, to more sophisticated global methods like Morris analysis or Sobol indices. Global methods are generally preferred as they consider the entire range of input uncertainties simultaneously and can account for interactions between variables. The choice of method depends on the complexity of the model, the number of input variables, and the desired level of detail in the analysis. Herkkyysanalyysi is widely applied in fields such as engineering, environmental science, economics, and risk assessment.