Error models play a central role in automated numerical analysis. Basically, when you have a floating-point operation x + y, it is usually easier to analyze it in terms of non-deterministic real operations. Epsilon and Delta The most common error model is that an operation x * y (taking * to be addition, subtraction, multiplication, or division, and sometimes square root or fused multiply-add) can be modeled with: \[ x \hat{*} y = (x * y) (1 + \varepsilon) \] Here, \(\hat{*}\) represents floa...
