Add three new continuous random variables for log-domain and
linear-domain clutter modeling with compound Gamma-Rice structure.
Fix numerical stability of k_dist._logpdf and logk._log_kve via a
three-regime log(kve) asymptotic (direct / large-z Hankel / large-order
Gamma); replace quad-based k_dist._cdf with Gauss-Laguerre quadrature.
Fix fitter: use np.asarray instead of np.abs in fit(), pass fit_params
to goodness_of_fit so the observed-data statistic reuses fitted params.
Skip non-finite quantiles in QQ plots. Add plot_qq_plots_sns(); rename
histogram_with_fits_seaborn() to histogram_with_fits_sns(). Add unit
tests for logweibull and logricegamma.
Introduce logk_gen (Y = ln X where X ~ K) with analytically derived
mean/variance via the CGF, numerically stable logpdf using an asymptotic
Bessel expansion for large arguments, CDF delegation to k_dist, and a
compound-gamma rvs sampler.
Add _rvs to k_dist via the same compound-gamma algorithm and extend
TestKDistPdf with stats and rvs coverage. Add a full TestLogK suite
covering pdf normalization, change-of-variable identity, CDF consistency,
analytical moment checks, and rvs moment checks.
Module-level docstring added to distributions.py
Add Log-Rayleigh and Log-Rice continuous distributions as
scipy rv_continuous subclasses with PDF, CDF, SF, PPF, ISF,
moments, entropy, and RVS methods.
Log-Rice reduces to Log-Rayleigh when nu=0. Both are derived
via the change-of-variable Y = ln X on their respective parent
distributions. Includes unit tests verifying numerical
correctness and the change-of-variable identity.
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
