Question
Let ,
and
be partitioned as
,
and
. Then derive the conditional distribution of
.
Answer :
Word Count : 321
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Skip in 10
Let ( X \sim N_p(\mu, \Sigma) ) be partitioned as [ X = \begin{pmatrix} X^{(1)} \ X^{(2)} \end{pmatrix}, \quad \mu = \begin{pmatrix} \mu^{(1)} \ \mu^{(2)} \end{pmatrix}, \quad \Sigma = \begin{pmatrix} \Sigma_{11} & \Sigma_{12} \ \Sigma_{21} & \Sigma_{22} \end{pmatrix}, ] where ( X^{(1)} ) is ( k \times 1 ) and ( X^{(2)} ) is ( (p-k) \times 1 ). We want the conditional distribution of ( X^{(2)} \mid X^{(1)} = x^{(1)} ). The joint density of ( X ) is [ f_X(x) = \frac{1}{(2\pi)^{p/2} |\Sigma|^{1/2}} \exp\Bigg{ -\frac{1}{2} (x-\mu)' \Sigma^{-1} (x-\mu) \Bigg}. ] Partition (\Sigma^{-1}) as [ \Sigma^{-1} = \begin{pmatrix} A & B \ C & D \end{pmatrix}. ] Then the quadratic form can be written as [ (x-\mu)' \Sigma^{-1} (x-\mu) = (x^{(1)}-\mu^{(1)})'
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