NEWS.md

In jpfitzinger/hfr: Estimate Hierarchical Feature Regression Models

hfr 0.5.0

• Note that this starts from version hfr 0.5.0.

hfr 0.6.0

• The plotting functionality has been expanded to highlight statistically insignificant branches
• Option to compute partial correlations using the pairwise (default) approach, or shrinkage approach
• Optional 'weights' argument to implement a weighted version of HFR.

hfr 0.6.1

• Add an optional level-specific ridge_lambda parameter to penalize level-specific regressions
• Rename 'kappa_grid' argument to 'kappa' in 'cv.hfr' (for consistency across different methods)
• Minor bugfixes

hfr 0.6.2

• Minor bugfixes in se.avg()

hfr 0.7.0

• Introduce handling of linearly dependent columns and columns with zero standard deviation in 'x'
• Rename argument 'ridge_lambda' to 'l2_penalty'
• Updated documentation

hfr 0.7.1

• fix handling of 'kappa' values < 1/k in the presence of intercept

jpfitzinger/hfr documentation built on March 1, 2024, 2:27 p.m.