What’s new in pmdarima¶

As new releases of pmdarima are pushed out, the following list (introduced in v0.8.1) will document the latest features.

v1.1.1 ¶

v1.1.1 is a patch release in response to #104

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.

Added ARIMA.plot_diagnostics method, as requested in #49
Added 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 Issue #54
ARIMA serialization no longer stores statsmodels results wrappers in the cache, but bundles them into the pickle file. This solves Issue #48 and only works on statsmodels 0.9.0+ since they’ve fixed a bug on their end.
The 'PMDARIMA_CACHE' and 'PMDARIMA_CACHE_WARN_SIZE' environment variables are now deprecated, since they no longer need to be used.
Added versioned documentation. All releases’ doc (from 0.9.0 onward) is now available at alkaline-ml.com/pmdarima/<version>
Fix bug in ADFTest where OLS was computed with method="pinv" rather than "method=qr". This fix means better parity with R’s results. See #71 for more context.
CHTest now solves linear regression with normalize=True. This solves #74
Python 3.7 is now supported(!!)

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 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'

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.
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.
Added Circle CI for validating PyPy builds (rather than CPython)
Deploy python wheel for version 3.6 on Linux and Windows
Include warning for upcoming package name change (pmdarima).

ARIMA instance attributes
- The pkg_version_ attribute (assigned on model fit) is new as of version 0.8.0. 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 (see Serializing your ARIMA models)
- Specifies the ARIMA result pickle name pattern
Fix bug (Issue #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.

out_of_sample_size behavior in pmdarima.arima.ARIMA
- In prior versions, the out_of_sample_size (OOSS) parameter misbehaved in the sense that it ended up fitting the model on the entire sample, and scoring the number specified. This behavior changed in v0.7.0. Going forward, when OOSS is not None, ARIMA models will be fit on \(n - OOSS\) samples, scored on the last OOSS samples, and the held-out samples are then added to the model.
add_new_samples method added to pmdarima.arima.ARIMA
- This method adds new samples to the model, effectively refreshing the point from which it creates new forecasts without impacting the model parameters.
Add confidence intervals on predict in pmdarima.arima.ARIMA
- When return_conf_int is true, the confidence intervals will now be returned with the forecasts.

pmdarima.arima.CHTest of seasonality
- No longer compute the \(U\) or \(V\) matrix in the SVD computation in the Canova-Hansen test. This makes the test much faster.