Simulate via inverse transform and Gibbs

Q: Simulate via inverse transform and Gibbs

This is a Statistics & Math interview question from Other for Data Scientist roles. View the full question and solution on PracHub.

Q: How do I approach Statistics & Math interview questions?

Statistics & Math questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master statistics & math interviews.

Question

Inverse transform: (a) Derive an algorithm to simulate from the Logistic(μ, s) distribution using its CDF and inverse CDF; show how to obtain samples for μ=0, s=1. (b) Give acceptance criteria to verify sample correctness (e.g., KS test) and discuss sample size needed. Gibbs sampling: Consider the joint density proportional to exp(−(x−y)^2/2)·exp(−x^2/2) for x, y ∈ R. (c) Derive the full conditional distributions p(x|y) and p(y|x) and specify a Gibbs sampler. (d) Explain how to diagnose convergence and choose burn-in and thinning.

Simulate via inverse transform and Gibbs

Comments (0)