Pmdarima

* Adds the `OCSBTest` of seasonality, as discussed in [88](https://github.com/tgsmith61591/pmdarima/issues/88)
* Default value of `seasonal_test` changes from "ch" to "ocsb" in `auto_arima`
* Default value of `test` changes from "ch" to "ocsb" in `nsdiffs`
* Adds benchmarking notebook and capabilities in `pytest` plugins
* Removes the following environment variables, which are now deprecated:
* `PMDARIMA_CACHE` and `PYRAMID_ARIMA_CACHE`
* `PMDARIMA_CACHE_WARN_SIZE` and `PYRAMID_ARIMA_CACHE_WARN_SIZE`
* `PYRAMID_MPL_DEBUG`
* `PYRAMID_MPL_BACKEND`
* Deprecates the `is_stationary` method in tests of stationarity. This will be removed in
v1.4.0. Use `should_diff` instead.
* Adds two new datasets: `airpassengers` & `austres`
* When using `out_of_sample`, the out-of-sample predictions are now stored
under the `oob_preds_` attribute.
* Adds a number of transformer classes including:
* `BoxCoxEndogTransformer`
* `FourierFeaturizer`
* Adds a `Pipeline` class resembling that of scikit-learn's, which allows the
stacking of transformers together.
* Adds a class wrapper for `auto_arima`: `AutoARIMA`. This is allows auto-ARIMA
to be used with pipelines.

* Deprecates the `ARIMA.add_new_observations` method. This method originally was designed to support updating the endogenous/exogenous arrays with new observations without changing the model parameters, but achieving this behavior for each of statsmodels' `ARMA`, `ARIMA` and `SARIMAX` classes proved nearly impossible, given the extremely complex internals of statmodels estimators.

* Replace `ARIMA.add_new_observations` with `ARIMA.update`. This allows the user to update the model with new observations by taking `maxiter` new steps from the existing model coefficients and allowing the MLE to converge to an updated set of model parameters.

* Change default `maxiter` to None, using 50 for seasonal models and 500 for non-seasonal models (as statsmodels does). The default value used to be 50 for all models.

* New behavior in `ARIMA.fit` allows `start_params` and `maxiter` to be passed as `**fit_args`, overriding the use of their corresponding instance attributes.

* `ARIMA.plot_diagnostics` method, as requested in 49
* Adds new arg to `ARIMA` constructor and `auto_arima`: `with_intercept` (default is True).
* New default for `trend` is no longer `'c'`, it is `None`.
* Added `to_dict` method to `ARIMA` class to address 54
* The `'PMDARIMA_CACHE'` and `'PMDARIMA_CACHE_WARN_SIZE'` environment variables are
now deprecated, since they no longer need to be used. They will be removed in v1.2.0
* Added versioned documentation. All releases' doc (from 0.9.0 onward) is now available
at `alkaline-ml.com/pmdarima/<version>`
* **Python 3.7 support(!!)**

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* **Wheels will no longer be built for Python versions < 3.5.** You may still be able to build
from source, but support for 2.x python versions will diminish in future versions.

* Migrate namespace from 'pyramid-arima' to 'pmdarima'. This is due to the fact that
a growing web-framework (also named Pyramid) is causing namespace collisions when
both packages are installed on a machine. See [Issue 34](https://github.com/tgsmith61591/pmdarima/issues/34)
for more detail.

* Remove redundant Travis tests

* Automate documentation build on Circle CI

* Move lots of the build/test functionality into the `Makefile` for ease.

* Warn for impending deprecation of various environment variable name changes. The following
will be completely switched over in version 1.2.0:

- `'PYRAMID_MPL_DEBUG'` will become `'PMDARIMA_MPL_DEBUG'`
- `'PYRAMID_MPL_BACKEND'` will become `'PMDARIMA_MPL_BACKEND'`
- `'PYRAMID_ARIMA_CACHE_WARN_SIZE'` will become `'PMDARIMA_CACHE_WARN_SIZE'`

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Bug fixes:

* Explicitly catch case in ``auto_arima`` where a value of ``m`` that is too large may over-estimate
``D``, causing the time series to be differenced down to an empty array. This is now handled by
raising a separate error for this case that better explains what happened.

* Re-pickling an ``ARIMA`` will no longer remove the location on disk of the cached ``statsmodels``
ARIMA models. Older versions encountered an issue where an older version of the model would be
reinstated and immediately fail due to an OSError since the cached state no longer existed. This
means that a user must be very intentional about clearing out the pyramid cache over time (addresses 39)

* Added pyramid cache check on initial import to warn user if the cache size has grown too large.

* If ``d`` or ``D`` are explicitly defined for ``auto_arima`` (rather than ``None``), do not
raise an error if they exceed ``max_d`` or ``max_D``, respectively (sort of addresses 37)

New features:

* Added Circle CI for validating PyPy builds (rather than CPython)

* Deploy python wheel for version 3.6 on Linux and Windows (addresses 38)

Forward looking

* Include warning for upcoming package name change (``pmdarima``).

* `ARIMA` instance attributes

- The `pkg_version_` attribute (assigned on model `fit`) is new as of version 0.8.1.
On unpickling, if the current Pyramid version does not match the version under which it
was serialized, a `UserWarning` will be raised.

* Addition of the `_config.py` file at the top-level of the package

- Specifies the location of the ARIMA result pickles
- Specifies the ARIMA result pickle name pattern

* Fix bug ([Issue 30](https://github.com/tgsmith61591/pyramid/issues/30)) in `ARIMA`
where using CV with differencing and no seasonality caused a dim mismatch in the model's
exog array and its endog array

* New dataset: woolyrnq (from R's `forecast` package).

* Visualization utilities available at the top level of the package:

- `plot_acf`
- `plot_pacf`
- `autocorr_plot`

* Updated documentation with significantly more examples and API references.