Mean integrated squared error
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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[1]
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.
See also[]
- Minimum distance estimation
- Mean squared error
References[]
- ^ Wand, M. P.; Jones, M. C. (1994). Kernel smoothing. CRC press. p. 15.
Categories:
- Estimation of densities
- Nonparametric statistics
- Point estimation performance