v0.6.3

New Features

• gridsearch(...) allows searching across a predefined grid of points, without doing the cartesian product, when grid is a np.ndarray of shape (n_points, len(flatten(gam.lam))). This is useful for RandomSearchCV - style behavior.

Bug Fixes

• estimate_r_squared(X, y) no longer raises AttributeError
• dtype=auto no longer allowed for terms
• intercept.lam = None

v0.6.1

New Features

• easier global arguments for terms

GAM(s(0) + s(1), n_splines=10).fit(X, y)

will broadcast n_splines=10 to all terms

Bug Fixes

• fixed inconsistencies in GAM instatiation, where

GAM(lam=0.6).gridsearch(X, y)

worked for multi-dimensional X

but not

GAM(lam=0.6).gridsearch(X, y)

v0.5.5

New Featrues

• all GAM classes have a verbose argument. this makes them compatible with sklearn GridsearchCV + RandomizedsearchCV
• add toy_classification dataset
• move generate_X_grid to GAM method

Bug Fixes

• users should get a more pythonic experience with partial_dependence by never needing to index with i+1
• _initial_estimate() method no longer fails on value nudge for purely integer observations
• regenerate images
• bugs in readme
• fixes bug where poorly conditioned matrix would fail when using skcholmod
• make2d should not be verbose in initial_estimate()

v0.5.4

Bug Fixes

• PoissonGAM no longer produces -inf log-likelihoods when using non-integer exposure.
• PoissonGAM checks exposure, weight, and y array shapes before fitting.

v0.5.3

Bug Fixes

• datasets are loadable like:

from pygam.datasets load cake
X, y = cake(return_X_y=True)

• better model initializations for complex models by using the solution to linear unpenalized problem. This makes the second order PIRLS optimizer less likely to diverge by overshooting the maximum likelihood estimate.
• ReadMe call for collaboration, examples reference dataset loaders, fix typos

v0.5.2

Bug Fixes

• bug fix in p-value for models with unknown variance. f-statistic was sensitive to estimated variance when it should be invariant.
• typos

v0.5.1

New Features:

• p-values!
• you can now see p-values in the model summary. each feature function will have a p-value, and a code describing it's level of significance.

Bug Fixes

• improving documentation

v0.4.2

Bug Fixes

• use scipy stats log-pdfs for computing log-likelihoods
• disable progress bars in gridsearch setting progress=False
• add verbosity attribute to GAMs to control warnings

v0.4.1

Bug Fixes:

• alow for changing SVD shapes during PIRLS iterations due to changing mask shapes
• change coefficient initialization to constant model
• change GammaGAM and InvGaussGAM to use non-canonical log-links by default.

v0.4.0

New Features

• all GAMs have a sample() method that samples:

  • response variables,
  • model coefficients,
  • and expected values from the posterior probability
    thanks to @cbrummitt !!! 🥇

• all distributions have a sample(mu) method

Bug fixes

• can now raise to negative power
• confidence and prediction intervals use correct degrees of freedom
• all public methods that accept data check for finite data

Improvements

• fixes to documentation