Add explicit-state Bernoulli distribution - #86
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The common
log_probpath has no concrete discrete distribution, so integer sampling, probability bounds, and discrete MLE remain unproven in the new API.This PR adds an opt-in Bernoulli law whose probability is a literal or parameter expression. It scores observations through
log_prob, offerspmf, returns integer samples with sample dimensions before parameter batches, and works with the existing explicit-state fitter. Invalid probability states are rejected during evaluation and penalized during fitting.Bernoulli lives with the SciPy-backed implementations, while
distributions/core.pyremains limited to shared contracts. Broader discrete wrappers and the public API cutover remain separate work.