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| − | Mean square | + | Mean square error : <math>MSE = E[(\theta - \hat \theta(x))^2]</math> |
==Linear Minimum Mean-Square Estimation (LMMSE)== | ==Linear Minimum Mean-Square Estimation (LMMSE)== | ||
Revision as of 16:36, 11 December 2008
Contents
Maximum Likelihood Estimation (ML)
Maximum A-Posteriori Estimation (MAP)
Minimum Mean-Square Estimation (MMSE)
$ {y}_{\rm MMSE}(x) \int\limits_{-inf}^{inf}\ {y}{f}_{\rm y|x}(Y|X=x)\, dy={E}(Y|X=x) $
$ {y}_{\rm LMMSE}(x)=E[\theta]+\frac{COV(x,\theta)}{Var(x)}*(x-E[x]) $
Mean square error : $ MSE = E[(\theta - \hat \theta(x))^2] $
Linear Minimum Mean-Square Estimation (LMMSE)
Hypothesis Testing: ML Rule
Type I error
Type II error
Hypothesis Testing: MAP Rule
Overall P(err)
