Pygam

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

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

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.

New Features
- all GAMs have a `sample()` method that samples:
- response variables,
- model coefficients,
- and expected values from the posterior probability
thanks to cbrummitt !!! :1st_place_medal:

- all distributions have a `sample(mu)` method

Bug fixes
- can now raise to [negative power](https://github.com/dswah/pyGAM/issues/133)
- confidence and prediction intervals use [correct degrees of freedom](https://github.com/dswah/pyGAM/issues/144)
- all public methods that accept data [check for finite data](https://github.com/dswah/pyGAM/issues/145)

Improvements
- fixes to documentation

New Features:

- GAMs accept weights in fitting, gridsearch, likelihood, statistics...
- PoissonGAM accepts exposure


Changes

- better handling of PIRLS weights
- check for isfinite(...).all() in check_X, check_y


Bug Fixes

- constant covariates won't break SVD