Joint distribution of exponential and uniform random variables

probability distributionsrandom variables

Suppose we have continuous random variable X with exponential distribution with parameter λ and continuous random variable Y with uniform distribution on an interval [$a$, X], where $a$ is some number and X is fixed.

How do we find the joint distribution function of X and Y?

Is it true that I have to break it up into cases like $x\le a$ and $y\le a$, and consider a product of the distribution functions of X and Y on the interval as their joint distribution function?

Best Answer

I assume that $a < 0$. The marginal distributions of ${\bf X}$ is:

$$f_{\bf X}(x) = \lambda e^{-\lambda x}.$$

The conditional distribution of ${\bf Y}$ knowing ${\bf X}$ is:

$$f_{\bf Y|\bf X}(y|x) = \begin{cases} \displaystyle\frac{1}{x-a} & \text{for}~y \in [a, x]\\ 0 & \text{otherwise} \end{cases}.$$

Notice that, the conditional distribution of ${\bf Y}$ knowing ${\bf X}$ is defined as:

$$f_{\bf{Y}|\bf{X}}(y|x) = \frac{f_{\bf{X},\bf{Y}}(x,y)}{f_{\bf{X}}(x)}.$$

Therefore:

\begin{align} f_{\bf{X},\bf{Y}}(x,y) & = f_{\bf{Y}|\bf{X}}(y|x)f_{\bf{X}}(x)\\ & = \begin{cases} \displaystyle\frac{\lambda e^{-\lambda x}}{x-a} & \text{for}~y \in [a, x]\\ 0 & \text{otherwise} \end{cases}& \end{align}