What is the distribution of X+Y when (X,Y) has bivariate normal distribution. I want to know the distribution of X+Y when (X,Y) has bivariate normal distribution and how to derive it.
What is the distribution of X+Y when (X,Y) has bivariate normal distribution.
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Let $X$ and $Y$ be jointly distributed as
$\left(\begin{array}{} X \\ Y \end{array} \right)\sim \mathcal N\left[\left(\begin{array}{} \mu_x \\ \mu_y \end{array} \right), \left(\begin{array}{} \sigma_x^2 & \rho \sigma_x\sigma_y\\ \rho \sigma_x\sigma_y & \sigma_y^2 \end{array} \right)\right]$
$\rho$ is the correlation coefficient. If $X$ and $Y$ are independent, then $\rho=0$.
The expected value of $Z=X+Y$ is $\mu_x+\mu_y$.
The variance of $Z$ is $Var(Z)=Var(X)+Var(Y)+2\cdot \rho \sigma_x\sigma_y$
Therefore $Z\sim\mathcal N\left( \mu_x+\mu_y,Var(X)+Var(Y)+2\cdot \rho \sigma_x\sigma_y\right)$
Thus the pdf is
$f_Z(z)=\frac{1}{\sqrt{2\pi}}\cdot \large{\frac{1}{\sqrt{\sigma_x^2+\sigma_x^2+2\cdot \rho \sigma_x\sigma_y}}}\cdot e^{\Large{-\frac{1}{2}\left(\frac{z-\mu_x-\mu_y}{\sqrt{\sigma_x^2+\sigma_x^2+2\cdot \rho \sigma_x\sigma_y}} \right)^2}}$
Multivariate normal distribution has the following property:
If $X:p\times 1\sim N_{p}(\mu,\Sigma)$, then for any vector $\alpha:p\times 1$ of constants, $\alpha'X\sim N_{1}(\alpha'\mu, \alpha'\Sigma\alpha)$.
So, the distribution is univariate normal, with $$E(X+Y)=\alpha'\mu$$ and $$Var(X+Y)=\alpha'\Sigma\alpha$$ where $\alpha'=(1,1)$.