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…nd fitting methods
- Implement rigorous tests for Bessel K_v, inverse incomplete gamma functions, and Student's t CDF in `test_special.py`. - Validate against scipy.special and scipy.stats with tight tolerances to catch known errors. - Introduce tests for sample skewness and kurtosis in `test_stats.py`, ensuring consistency with scipy.stats. - Create extensive tests for all 11 univariate distributions in `test_univariate.py`, covering logpdf, CDF, stats, fitting, and edge cases. - Include checks for PDF integration, inverse consistency, parameter recovery, and gradient correctness. - Address specific findings related to Student-T and IG distributions to ensure accuracy and reliability.
…m_hat and v_hat calculations
…or accurate statistics
…d accuracy using log_kv
…ccurate statistics
…on and improve stability using log_kv
…mproved performance and stability
… precision and stability; enhance initial approximation and Newton-Halley refinement process.
…ts for extreme values and refine tolerance levels for better precision.
…e using method of moments
… handling; add explicit normalization for total PDF integral to ensure accurate results.
…initial estimates; replace kv with log_kv for stability and add sample moments computation.
…g_kv for stability, add expected value computations, and implement negative log-likelihood gradient calculation.
…likelihood computation and update fit method to support EM approach.
…ctor _fit_mle and _fit_ldmle to use sample moments for better convergence.
… _sample_moments method and update _fit_mle to use these estimates for improved fitting.
…re functions for improved parameter estimation.
…special for accuracy and properties.
… enhance fit method to support MOM and MLE options.
… sampling accuracy
…g and GoF filtering
…vior more explicitly
…e, multivariate, and copula distributions
…, enhance clarity, and fix p-value calculations.
…ding references, and enhance clarity in assertions.
- Implemented `_cdf_grid_piecewise` to compute CDF values at a sorted grid of x values using a fixed 16-point Gauss-Legendre quadrature, improving performance for dense grids. - Updated `_cdf` to utilize the new piecewise CDF computation method. - Enhanced `_cubic_ppf_solve` to dispatch between numerical and closed-form CDF evaluations, leveraging `_cdf_grid_piecewise` for numerical distributions. - Introduced `warm_bounds` parameter in PPF functions to optimize bracket discovery during iterative fitting loops, reducing computational overhead.
…and sampling tests
… for PDF, CDF, and parameter fitting
… high lambda/μ regime
…AsymGenNormal classes
…ributions and tests
- Introduced `DataScaler` class for affine rescaling of input data with methods: z-score, min-max, robust, and max-abs. - Implemented `fit`, `transform`, and `inverse_transform` methods, ensuring compatibility with JAX's JIT, grad, and vmap. - Added comprehensive tests covering various aspects including round-trip identity, method-specific statistics, new-data stability, zero-variance safety, and integration with `copulax.univariate.Normal`. - Created documentation for preprocessing module and DataScaler class.
…ng methods and tests
- Introduced `gh_reference_data.py` containing auto-generated reference data for generalized hyperbolic and skewed-t distributions. - Implemented `test_multivariate_reference.py` to validate logpdf and pdf of `mvt_gh` and `mvt_skewed_t` against the R ghyp package. - Enhanced `test_copulas_elliptical.py` with manual Sklar verification for Student-t copula. - Updated `test_univariate.py` to include edge case tests for logpdf and cdf behavior at support boundaries. - Added tests for skewed-t distribution against scipy's genhyperbolic limit.
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test_special.py.test_stats.py, ensuring consistency with scipy.stats.test_univariate.py, covering logpdf, CDF, stats, fitting, and edge cases.