API: mcmc_sample

from optimizr import mcmc_sample

samples = mcmc_sample(
    log_likelihood_fn,
    data,
    initial_params,
    param_bounds,
    n_samples=10000,
    burn_in=1000,
    proposal_std=0.1,
)

• log_likelihood_fn(params, data) -> float

• data: np.ndarray passed through to the likelihood

• initial_params: np.ndarray starting point

• param_bounds: list of (min, max) tuples

• Returns samples: np.ndarray of shape (n_samples, n_params)