Conditional distribution of Normal r.v.

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Let X be N($\mu$,Q) with $\mu$= (1,1) and Q= $\begin{bmatrix} 3 & 1 \\ 1 & 2 \\ \end{bmatrix}$. I would like to find the distribution of Y = $X_1 + X_2$ given Z = $X_1 - X_2 = 0$ .

Therefore I should obtain that Y = $2X_1$ or, equally, that Y = $2X_2$, but since they have a different variance I don't understand how it could be possible.

Continuing with the solution I should find $f_{Z=0}(y)$ being normal with $\mu=2$ and $\sigma^2=20/3$. But still I'm not able to obtain this result. Could someone help?

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All variables in your problem are normal, therefore all the information you need is encoded in the covariance matrix (and means).

You can first compute: $$Var(Y) = Var(X_1+X_2) = 3 + 2 + 2 = 7$$ and $$Var(Z) = Var(X_1-X_2) = 3 + 2 - 2 = 3$$ and finally: $$Cov(Y,Z) = Cov(X_1+X_2,X_1-X_2) = 3 - 1 + 1 - 2 = 1$$ This gives joint distribution of $Y,Z$ being normal $ \mathcal{N}((2,0), \begin{bmatrix} 6 & 5 \\ 5 & 4 \\ \end{bmatrix} ) $

From this you can find pdf of $Y|Z=0$ explicitly and read off mean and variance.