…commit

* Fixed pep8
* Fixed flake8
* Rename GeneralizedLinearModel as GeneralizedLinearRegressor
* Use of six.with_metaclass
* PEP257: summary should be on same line as quotes
* Docstring of class GeneralizedLinearRegressor: \ before mu
* Arguments family and link accept strings
* Use of ConvergenceWarning

* GeneralizedLinearRegressor added to doc/modules/classes.rst

* fixed bug: init parameter max_iter
* fix API for family and link:
  default parameter changed to string
  non public variables self._family_instance and self._link_instance
* fixed bug in score, minus sign forgotten
* added check_is_fitted to estimate_phi and score
* added check_array(X) in predict
* replaced lambda functions in TweedieDistribution
* some documentation

* make raw docstrings where appropriate
* make ExponentialDispersionModel (i.e. TweedieDistribution) pickable:
  ExponentialDispersionModel has new properties include_lower_bound,
  method in_y_range is not abstract anymore.
* set self.intercept_=0 if fit_intercept=False, such that it is always defined.
* set score to D2, a generalized R2 with deviance instead of squared error,
  as does glmnet. This also solves issues with
  check_regressors_train(GeneralizedLinearRegressor), which assumes R2 score.
* change of names: weight to weights in ExponentialDispersionModel and to
  sample_weight in GeneralizedLinearRegressor
* add class method linear_predictor

* added L2 penalty
* api change: alpha, l1_ratio, P1, P2, warm_start, check_input, copy_X
* added entry in user guide
* improved docstrings
* helper function _irls_step

* fix some bugs in user guide linear_model.rst
* fix some pep8 issues in test_glm.py

* added test: ridge poisson with log-link compared to glmnet
* fix ValueError message for l1_ratio
* fix ValueError message for P2
* string comparison: use '==' and '!=' instead of 'is' and 'is not'
* fix RuntimeWarnings in unit_deviance of poisson: x*log(x) as xlogy
* added test for fisher matrix
* added test for family argument

* put arguments P1, P2 and check_input from fit to __init__
* added check_input test: is P2 positive definite?
* added solver option: 'auto'

* added coordinate descent solver
* skip doctest for GeneralizedLinearRegressor example
* symmetrize P2 => use P2 = 1/2 (P2+P2')
* better validation of parameter start_params

* bug for sparse matrices for newton-cg solver, function grad_hess
* reduce precision for solver newton-cg in test_poisson_ridge
* remedy doctest issues in linear_model.rst for example of GeneralizedLinearRegressor
* remove unused import of xrange from six

* bug in cd solver for sparse matrices
* higer precision (smaller tol) in test_normal_ridge for sparse matrices
* for each solver a separate precision (tol) in test_poisson_ridge

* improved documentation
* additional option 'zero' for argument start_params
* validation of sample_weight in function predict
* input validation of estimate_phi
* set default fit_dispersion=None
* bug in estimate_phi because of weight rescaling
* test for estimate_phi in normal ridge regression
* extended tests for elastic net poisson

* new helper function _check_weights for validation of sample_weight
* fix white space issue in doctest of linear_model.rst

* fit_dispersion default=None also in docs.
* improved docs.
* fixed input validation of predict
* fixed bug for sample_weight in estimate_phi

* improved docs

* fixed input validation of X in predict

* redundant line of code 'd = np.zeros_like(coef)'

* added test to compare to ElasticNet
* deleted identical comment lines

* increased precision in test_normal_enet

* better doc for heavy tailed distributions

* improved input validation and testing of them

* improved input validation and testing of P1
* test case for validation of argument P2
* test case for validation of argument copy_X

* fix doctest failure in example of linear_model.rst

* fix dtype issue in test_glm_P2_argument

* fix typos in doc

…spsolve about usage of umfpack

Co-Authored-By: Thomas J Fan <thomasjpfan@gmail.com>