Implement two new scipy-compatible distributions : Log-Nakagami
(lognakagami) and Log-Gamma (loggamma_dist), with complete
logpdf/cdf/ppf/stats/entropy/rvs methods derived from the
change-of-variable Y = ln(X).
Add kl_statistic, a KDE-based KL-divergence goodness-of-fit callable
compatible with the Fitter class. Extend k_gen with _stats (improving speed), _cdf, and
a fit guard, and switch kv → kve to improve numerical stability at large arguments.
Add unit tests for all three additions covering normalization,
monotonicity, ppf inversion, moment formulas, and Fitter integration.
ruff for code formatting
BIC statistic AND BIC test implemented
test_distributions.py for test new created dists with pytest
REFACTOR:
k_gen pdf changed from 2 params to generalized
`generate_data.py` for processing and fitting statistical distributions to data.
'distributions.py' to create new dists to fit
'analysis_data.ipynb" notebook for data analysis
