elidepb/Markov-Chain-Monte-Carlo-Method-MCMC-using-Python-and-R
View on GitHub ↗Related repositories →Explore the Markov Chain Monte Carlo (MCMC) method with Python and R. Includes implementations of Gibbs sampling, Metropolis-Hastings, and more. Perfect for Bayesian inference, parameter estimation, and probabilistic modeling. Dive into real-world examples with well-documented code.
active 2025-01-27 → 2025-01-28 (UTC)
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Line chart, 2 days from 2025-01-27 to 2025-01-28. Pushes: 3 total, peak 2 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
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Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| elidepb | 3 | 3 | 0 | 0 |
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Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.