MISE

MISE

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 \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. Here, E denotes the expected value with respect to that sample. The MISE is also known as L2 risk function.

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