Assume I sample N times from a geometric distribution with a known p i.e samples=np.random.geometric(p, size=N). How can I calculate weights p_prime(x) using p in such I way that sampling with replacement (while giving more weight to less common values) results in a unifrom discrete distribution i.e. np.random.choice(samples, size=N, replace=True, p=p_prime).
2026-04-01 03:24:18.1775013858
Discrete Uniform distribution from geometric samples.
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