Mean integrated squared error

In statistics, the mean integrated squared error (MISE) is used in density estimation. The MISE of an estimate of an unknown probability density is given by E ⁡ ‖ f n − f ‖ 2 2 = E ⁡ ∫ ( f n ( x ) − f ( x ) ) 2 d x {\displaystyle \operatorname {E} \|f_{n}-f\|_{2}^{2}=\operatorname {E} \int (f_{n}(x)-f(x))^{2}\,dx} where ƒ is the unknown density, ƒn is its estimate based on a sample of n independent and identically distributed random variables.

Source: Wikipedia — Mean integrated squared error (CC BY-SA 4.0)