Parameter uncertainty can be quantified using various statistical methods:
Confidence Intervals: These provide a range of plausible values for a parameter, reflecting the degree of uncertainty. Bayesian Methods: These incorporate prior knowledge and data to produce a probability distribution of parameter values. Sensitivity Analysis: This method assesses how changes in parameter values affect model outputs, helping to identify which parameters are most influential.
