* Allow both both hoidays and append holidays
Match holidays in predict and fit
Add test for append_holiday features; minor fixes
Add column name validation for append_holidays names; allow only one country
Fix bug about holiday year different from input year and also other bugs
Change function description
Add append holiday feature for R
* Add test for R/Pyrhon; fix bugs
* Allow both both hoidays and append holidays; match holidays in predict and fit
* Allow both both hoidays and append holidays; match holidays in predict and fit
* Add test for append_holiday features; minor fixes
* Add column name validation for append_holidays names; allow only one country
If this is installed on a 32-bit system (rare nowadays, but they still exist) then the conversion to `int` from `timedelta64[ns]` in `plot_cross_validation_metric` will fail. This patch explicitly uses an `np.int64` for this conversion.
* adding changes to python error metrics to new branch
* adding diagnosts to a new base branch v0.3
* adding code with broken out function definitions for each metric and handling of model for calculating insample and outsample metrics.
* Update memory requirement description per #326
* Fix R warning with extra regressor; disallow constant extra regressors.
* Fix unit test broken in new pandas
* Fix diagnostics unit tests for new pandas
* Fix copy with extra seasonalities / regressors Py
* Fix copy with extra seasonalities / regressors R
* Fix weekly_start and yearly_start in R plot_components
* Fix plotting in pandas 0.21 by using pydatetime instead of numpy
* Version bump
* Update README for new version
* Fix missing columns in SHF with extra regressor
* Update memory requirement description per #326
* Fix R warning with extra regressor; disallow constant extra regressors.
* Fix unit test broken in new pandas
* Fix diagnostics unit tests for new pandas
* Fix copy with extra seasonalities / regressors Py
* Fix copy with extra seasonalities / regressors R
* Fix weekly_start and yearly_start in R plot_components
* Fix plotting in pandas 0.21 by using pydatetime instead of numpy
