均方误差是衡量贝叶斯估计的性能指标之一，若\(\hat A\)是基于观测量\(z\)对\(A\)的贝叶斯估计，则\(Mse(\hat A)\)的表达式是 A: （A）\(Mse(\hat A) = E\left[ {{{(A - \hat A)}^2}} \right] = \int_{ - \infty }^\infty {{{(A - \hat A)}^2}p(z;A)dz} \)； B: （B）\(Mse(\hat A) = E\left[ {{{(A - \hat A)}^2}} \right] = \int_{ - \infty }^\infty {{{(A - \hat A)}^2}p(A)dA} \) C: （C）\(Mse(\hat A) = E\left[ {{{(A - \hat A)}^2}} \right] = \int_{ - \infty }^\infty {\int_{ - \infty }^\infty {{{(A - \hat A)}^2}p} } (z,A)dzdA\) D: （D）\(Mse(\hat A) = E\left[ {{{(A - \hat A)}^2}} \right] = \int_{ - \infty }^\infty {\int_{ - \infty }^\infty {{{(A - \hat A)}^2}p} } (A{\rm{|}}z)dzdA\)
均方误差是衡量贝叶斯估计的性能指标之一，若\(\hat A\)是基于观测量\(z\)对\(A\)的贝叶斯估计，则\(Mse(\hat A)\)的表达式是 A: （A）\(Mse(\hat A) = E\left[ {{{(A - \hat A)}^2}} \right] = \int_{ - \infty }^\infty {{{(A - \hat A)}^2}p(z;A)dz} \)； B: （B）\(Mse(\hat A) = E\left[ {{{(A - \hat A)}^2}} \right] = \int_{ - \infty }^\infty {{{(A - \hat A)}^2}p(A)dA} \) C: （C）\(Mse(\hat A) = E\left[ {{{(A - \hat A)}^2}} \right] = \int_{ - \infty }^\infty {\int_{ - \infty }^\infty {{{(A - \hat A)}^2}p} } (z,A)dzdA\) D: （D）\(Mse(\hat A) = E\left[ {{{(A - \hat A)}^2}} \right] = \int_{ - \infty }^\infty {\int_{ - \infty }^\infty {{{(A - \hat A)}^2}p} } (A{\rm{|}}z)dzdA\)
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