Version 1.3.0

Version 1.3.0

Major changes:

1. Add fractional polynomials basis function
2. Rename NLL (negative log-likelihood) → MLL (mean log-loss)
3. Add MACE averaging (as defined in Zamanzadeh et al. (2026))
4. Add kurtosis and skewness as evaluation metrics
5. Add migration strategy for saved models
6. Make HBR SHASHb faster by adjusting the dp parameter
7. Manage matplotlib more flexibly
8. Refactor BLR tutorial
9. Add federated learning and evaluation metrics tutorials
10. Update merge tutorial

Minor changes:

1. Update contributing guidelines and add rules in github (Issue and PR templates)

Bug fixes

1. Add add upper bounds for pymc, nutpie and pytensor
2. Fix HBR SHASH to return mean and second moment in m1m2()
3. Add h5py and h5netcdf as dependency in toml