Conditional distribution between jointly normal and univariate normal random variables












0












$begingroup$


Let $X = (X_1, X_2, X_3)^Tsim N_3(mu, Sigma)$, where



$$mu = begin{pmatrix}
1 \
1 \
1 \
end{pmatrix}, Sigma = begin{pmatrix}
1 & 1 & 0 \
1 & 2 & 1 \
0 & 1 & 2 \
end{pmatrix} $$



I want to find $(X_1, X_2)^T|X_3$.



I know that $(X_1, X_2)^T sim N_2(begin{pmatrix}
1\
1 \
end{pmatrix}, begin{pmatrix}
1 & 1 \
1 & 2 \
end{pmatrix})$
and that $X_3 sim N_1(1, 2)$.



My definition of conditional distribution of MVN however initially requires the distribution of $((X_1, X_2)^T, X_3)$, of which I am not sure.



Is there another way around this that I am missing? Thanks for your help.










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$endgroup$












  • $begingroup$
    Cross posted at stats.stackexchange.com/q/384280/119261.
    $endgroup$
    – StubbornAtom
    Dec 24 '18 at 5:51
















0












$begingroup$


Let $X = (X_1, X_2, X_3)^Tsim N_3(mu, Sigma)$, where



$$mu = begin{pmatrix}
1 \
1 \
1 \
end{pmatrix}, Sigma = begin{pmatrix}
1 & 1 & 0 \
1 & 2 & 1 \
0 & 1 & 2 \
end{pmatrix} $$



I want to find $(X_1, X_2)^T|X_3$.



I know that $(X_1, X_2)^T sim N_2(begin{pmatrix}
1\
1 \
end{pmatrix}, begin{pmatrix}
1 & 1 \
1 & 2 \
end{pmatrix})$
and that $X_3 sim N_1(1, 2)$.



My definition of conditional distribution of MVN however initially requires the distribution of $((X_1, X_2)^T, X_3)$, of which I am not sure.



Is there another way around this that I am missing? Thanks for your help.










share|cite|improve this question









$endgroup$












  • $begingroup$
    Cross posted at stats.stackexchange.com/q/384280/119261.
    $endgroup$
    – StubbornAtom
    Dec 24 '18 at 5:51














0












0








0


0



$begingroup$


Let $X = (X_1, X_2, X_3)^Tsim N_3(mu, Sigma)$, where



$$mu = begin{pmatrix}
1 \
1 \
1 \
end{pmatrix}, Sigma = begin{pmatrix}
1 & 1 & 0 \
1 & 2 & 1 \
0 & 1 & 2 \
end{pmatrix} $$



I want to find $(X_1, X_2)^T|X_3$.



I know that $(X_1, X_2)^T sim N_2(begin{pmatrix}
1\
1 \
end{pmatrix}, begin{pmatrix}
1 & 1 \
1 & 2 \
end{pmatrix})$
and that $X_3 sim N_1(1, 2)$.



My definition of conditional distribution of MVN however initially requires the distribution of $((X_1, X_2)^T, X_3)$, of which I am not sure.



Is there another way around this that I am missing? Thanks for your help.










share|cite|improve this question









$endgroup$




Let $X = (X_1, X_2, X_3)^Tsim N_3(mu, Sigma)$, where



$$mu = begin{pmatrix}
1 \
1 \
1 \
end{pmatrix}, Sigma = begin{pmatrix}
1 & 1 & 0 \
1 & 2 & 1 \
0 & 1 & 2 \
end{pmatrix} $$



I want to find $(X_1, X_2)^T|X_3$.



I know that $(X_1, X_2)^T sim N_2(begin{pmatrix}
1\
1 \
end{pmatrix}, begin{pmatrix}
1 & 1 \
1 & 2 \
end{pmatrix})$
and that $X_3 sim N_1(1, 2)$.



My definition of conditional distribution of MVN however initially requires the distribution of $((X_1, X_2)^T, X_3)$, of which I am not sure.



Is there another way around this that I am missing? Thanks for your help.







probability-distributions random-variables normal-distribution conditional-probability






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share|cite|improve this question











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asked Dec 23 '18 at 12:23









JasonJason

82




82












  • $begingroup$
    Cross posted at stats.stackexchange.com/q/384280/119261.
    $endgroup$
    – StubbornAtom
    Dec 24 '18 at 5:51


















  • $begingroup$
    Cross posted at stats.stackexchange.com/q/384280/119261.
    $endgroup$
    – StubbornAtom
    Dec 24 '18 at 5:51
















$begingroup$
Cross posted at stats.stackexchange.com/q/384280/119261.
$endgroup$
– StubbornAtom
Dec 24 '18 at 5:51




$begingroup$
Cross posted at stats.stackexchange.com/q/384280/119261.
$endgroup$
– StubbornAtom
Dec 24 '18 at 5:51










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