Mean Integrated Squared Error

In statistics, the mean integrated squared error (MISE) is used in density estimation. The MISE of an estimator, estimate of an unknown probability density function, probability density is given by

:$\operatorname\, f_n-f\, _2^2=\operatorname\int (f_n(x)-f(x))^2 \, dx$

where ''ƒ'' is the unknown density, ''ƒ''_''n'' is its estimate based on a sample (statistics), 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 ''L''² risk function.

See also

* Minimum distance estimation
* Mean squared error

References

{{DEFAULTSORT:Mean Integrated Squared Error
Estimation of densities
Nonparametric statistics
Point estimation performance