This chapter concerns principles and methods for sensitivity analyses that quantify the robustness of inferences to departures from underlying assumptions. Unlike the well-developed literature on ...

Climate extremes have major impacts on the terrestrial carbon cycle 1,2,3. Climate models project increases in the frequency and severity of prominent climate extremes such as drought 3,7,8. Thus, the ...

Hydrologic models are widely used in applications that are important for society such as flood prediction 1,2,3,4,5,6, drought monitoring 7,8,9,10, infrastructure design 11,12,13, and reservoir ...

Sensitivity analysis helps predict outcomes by varying key variables in financial models. It simplifies complex models, aids in understanding variable effects, and reduces uncertainty. This analysis ...

Both variance and sensitivity analyses provide useful information to managers of small companies as they seek to increase company performance and reduce the company's risks. While both forms of ...