Normalizing a joint PDF $f(x,y)$ and finding the marginal PDF’s $f_X(x) $ and $f_Y(y)$

density functionmarginal-distributionprobability distributions

I have the following joint PDF:

$$f_{UV}(u,v):= C \cdot \unicode[STIXGeneral]{x1D7D9}_{\{ (u,v): 0\le u \le 1, u \le v \le u+1 \}}(u,v)$$

(In case the subscript of the indicator function is a bit hard to read: $\{ (u,v): 0\le u \le 1, u \le v \le u+1 \}$)

I want to determine $C$ so this function can be considered a PDF. In other words, I need to show that:

$$\int_{-\infty}^{\infty}\int_{-\infty}^{\infty}f(x,y)dxdy=1$$


Here is my first problem:

I am having difficulties converting the subscript from the indicator function into an integral. My attempt:

$$C\int_0^1 \int_u^{u+1}1 \space dvdu=C\int_0^1 (v)\lvert_{u}^{u+1}du=C\int_0^11du=C$$

So in order for this to be normalized and satisfy the property, $C=1$. Is this correct or am I misreading the bounds from the indicator function?


Here is my second problem:

I want to determine the marginal PDF's $f_X$ and $f_Y$ from the joint PDF. I know this can be achieved by integrating over the "other" variable. For $f_Y$ the formula is:

$$\begin{align}%
\\
f_Y(y)=\int_{-\infty}^{\infty} f_{XY}(x,y)dx, \hspace{10pt} \textrm{ for all }y.
\end{align}$$

Similar problem to the first problem. My bounds are not independent from each other so I am not sure how to write the integral. How do I set up my bounds here? My attempt:

$$f_Y=\int_0^21dx=2 \\ \implies f_Y= \begin{cases}2 \hspace{10pt} \text{for} \hspace{10pt} 0 \le y\le2 \\ 0 \hspace{10pt} \text{else}\end{cases}$$

Is this correct?

Best Answer

The indicator is clear...what is wrong is that you have $f(u,v)$ and not $f(x,y)$

The support is a parallelogram (do a drawing to realize that) with area $1$ thus your density is uniform over this parallelogram and $C=1$, the reciprocal of the support area. No integrals are needed.

enter image description here

To get the two marginals you have to integrate

  • $f_U(u)=\int_u^{u+1}dv=1$

That is $U\sim U(0;1)$

For $V$ you have to observe that,

  • when $v \in(0;1)$ you have

$$f_V(v)=\int_0^v du=v$$

  • when $v \in[1;2)$ you have

$$f_V(v)=\int_{v-1}^1 du=2-v$$

concluding, $f_V$ is a triangular density

This is a compact way to write it

$$f_V(v)=[1-|1-v|]\mathbb{1}_{(0;2)}(v)$$

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