2
$\begingroup$

Consider a random vector $U = (U_1,U_2)$ where $U_1$ and $U_2$ are independent and identically distributed. Let $X =(X_1,X_2)$ with $X_1$ and $X_2$ being dependent random variables.

Suppose that $X = (X_1,X_2)$ and $U = (U_1,U_2)$ are independent. Define $Z_1 = X_1 U_1$ and $Z_2 = X_2 U_2$. The question at hand is to determine whether the variables $Z_1$ and $Z_2$ are independent.

Attempt: To investigate the independence of $Z_1$ and $Z_2$, we need to analyze their joint distribution. Let $f_{Z_1,Z_2}(z_1,z_2)$ denote the joint distribution of $Z_1$ and $Z_2$. We can express this joint distribution as:

$$f_{Z_1,Z_2}(z_1,z_2) = \int_{-\infty}^{\infty} f_{X_1,X_2}(z_1/u_1,z_2/u_2) \, f_{U_1,U_2}(u_1,u_2) \, du_1 \, du_2.$$

If this expression does not factorize into the product of the marginal distributions of $Z_1$ and $Z_2$, then $Z_1$ and $Z_2$ are not independent.

Is there a counterexample or is this true?

$\endgroup$
0

1 Answer 1

2
$\begingroup$

Certainly they're not independent in general. Here's a counterexample where the covariance of the $Z$'s will not be zero and hence they cannot be independent.

Suppose all the relevant expectations are finite:

\begin{eqnarray} \text{Cov}(X_1 U_1, X_2 U_2) &=& E(X_1 X_2 U_1 U_2) - E(X_1 U_1) E(X_2 U_2)\\ &=& E(X_1 X_2) E(U_1) E(U_2) - E(X_1) E(U_1) E(X_2) E(U_2)\\ &=& E(U_1)E(U_2) \text{Cov}(X_1,X_2) \end{eqnarray}

which is only zero when one of those terms is $0$, which we can readily construct so as not to be the case.

e.g. make $U$'s standard uniform and let $X_1=X_2$ also be standard uniform. We could proceed algebraically of course but all we really need is to double check that the above argument works, so a simulation will do:

 n=10000
 u1=runif(n);u2=runif(n);x1=runif(n);x2=x1
 cor(u1*x1,u2*x2)
 [1] 0.4271108

Visually the dependence between $Z_1$ and $Z_2$ isn't super strong in this example (unless you know what you're looking for), but you can very clearly see it in their square roots:

plot of sqrt(Z2) vs sqrt(Z1) showing clear correlation

When looking for counterexamples, often just thinking of very simple possibilities can be fruitful.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.