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Risk function
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The risk of an estimator is its expected loss as a function of the unknown parameter. Under quadratic loss,
R
(
θ
,
δ
)
=
E
θ
[(
δ
−
θ
)
2
]
=
Var
θ
(
δ
)
+
(
E
θ
δ
−
θ
)
2
.
(194)
Table of contents
110
5
Mean squared error
Risk function
49
2
Bias-variance decomposition of mean squared error
Mean squared error
10
Affine shrinkage estimator for a binomial proportion
Mean squared error
27
Admissible estimator
Risk function
24
Minimax estimator
Risk function
13
Ancestors
(5)
Statistical modelling
Probability and statistics
Area of mathematics
Mathematics
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