# global sensitivity analysis

Sensitivity analysis

## What is variance-based sensitivity analysis?

Variance-based sensitivity analysis is a form of global sensitivity analysis based on a decomposition of the variance of the model output.

Sensitivity analysis

## What are the total-effect sensitivity indices?

A total-effect sensitivity index quantifies the effect of the associated model parameter and all its interactions with other parameters on the model output. The total-effect sensitivity indices are well-suited for factor fixing.

Sensitivity analysis

## How to evaluate the first-order sensitivity indices numerically?

Based on samples from a Monte Carlo simulation, the first-order sensitivity indices can be estimated without additional model calls. This requires the numerical approximation of a one-dimensional conditional expectation.

Sensitivity analysis

## What is an additive model?

For additive models, the variance of the model output can be decomposed as the sum of the first-order effects of the model input.

Sensitivity analysis

## What are the first-order sensitivity indices?

A first-order sensitivity index quantifies the effect of varying the associated model input parameter alone. The first-order sensitivity indices are well-suited for factor prioritization.

Sensitivity analysis

## How can we decompose the variance of the model output?

We can decompose the variance of the model output in terms of a series expansion of combined effects if the model input parameters are statistically independent.

Sensitivity analysis

## Can scatter plots be used for sensitivity analysis?

Scatter plots of the input against the output are one of the simplest and most versatile tools for qualitative global sensitivity analysis.