0
$\begingroup$

Let $X \sim F(;\theta)$ and $Y \sim G(;\eta)$ be two independent continuous random variables. The greek symbols represent the parameters of those distributions. I can easily sample from these distributions.

Let $(\tilde{X},\tilde{Y}) \sim H(;\kappa)$. These variables are not independent. In fact, I know the conditional distribution of $\tilde{X}\mid \tilde{Y}$ and the marginal distribution of $\tilde{Y}$.

For specific parameter values $\theta$ and $\eta$, how can I find the parameters $\kappa$ that better approximate (in any sense computationally feasible, KL divergence, TV, etcetera) the distribution of $(X,Y)$?

Improve this question
$\endgroup$
2
  • 1
    $\begingroup$ It might help to define your symbols, such as $\tilde{X}$ $\endgroup$ Commented Sep 7, 2023 at 11:01
  • $\begingroup$ Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking. $\endgroup$ Commented Sep 7, 2023 at 11:09

0

Reset to default

Your Answer

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

Start asking to get answers

Find the answer to your question by asking.

Ask question

Explore related questions

See similar questions with these tags.