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4.0.txt
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4.0.txt
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Changes since 4.8.1
===================
- Added :func:`~arch.univariate.base.ARCHModelResult.optimization_result` to
simplify checking for convergence of the numerical optimizer (:issue:`292`).
- Added `random_state` argument to :func:`~arch.univariate.HARX.forecast`
to allow a :class:`~numpy.random.RandomState` object to be passed in when
forecasting when `method='bootstrap'`. This allows the repeatable forecast to
be produced (:issue:`290`).
- Fixed a bug in :class:`~arch.unitroot.VarianceRatio` that used the wrong
variance in nonrobust inference with overlapping samples (:issue:`286`).
Release 4.8.1
=============
- Fixed a bug which prevented extension modules from being correctly imported.
Release 4.8
===========
- Added Zivot-Andrews unit root test :class:`~arch.unitroot.ZivotAndrews`.
This code was originally written by Jim Varanelli.
- Added data dependent lag length selection to the KPSS test,
:class:`~arch.unitroot.KPSS`. This code was originally written by
Jim Varanelli.
- Added :class:`~arch.bootstrap.IndependentSamplesBootstrap` to
perform bootstrap inference on statistics from independent samples that may
have uneven length (:issue:`260`).
- Added :func:`~arch.univariate.base.ARCHModelResult.arch_lm_test` to
perform ARCH-LM tests on model residuals or standardized residuals
(:issue:`261`).
- Fixed a bug in :class:`~arch.unitroot.ADF` when applying to very short time series
(:issue:`262`).
- Added ability to set the ``random_state`` when initializing a bootstrap
(:issue:`259`).
Release 4.7
===========
- Added support for Fractionally Integrated GARCH (FIGARCH) in
:class:`~arch.univariate.FIGARCH`.
- Enable user to specify a specific value of the `backcast` in place of
the automatically generated value.
- Fixed a big where parameter-less models where incorrectly reported as
having constant variance (:issue:`248`).
Release 4.6
===========
- Added support for MIDAS volatility processes using Hyperbolic
weighting in :class:`~arch.univariate.MidasHyperbolic`
(:issue:`233`).
Release 4.5
===========
- Added a parameter to forecast that allows a user-provided callable random
generator to be used in place of the model random generator (:issue:`225`).
- Added a low memory automatic lag selection method that can be used with very
large time-series.
- Improved performance of automatic lag selection in ADF and related tests.
Release 4.4
===========
- Added named parameters to Dickey-Fuller regressions.
- Removed use of the module-level NumPy RandomState. All random number
generators use separate RandomState instances.
- Fixed a bug that prevented 1-step forecasts with exogenous regressors.
- Added the Generalized Error Distribution for univariate ARCH models.
- Fixed a bug in MCS when using the max method that prevented all included
models from being listed.
Release 4.3
===========
- Added :class:`~arch.univariate.FixedVariance` volatility process which
allows pre-specified variances to be used with a mean model. This has been
added to allow so-called zig-zag estimation where a mean model is estimated
with a fixed variance, and then a variance model is estimated on the residuals
using a ``ZeroMean`` variance process.
Release 4.2
===========
- Fixed a bug that prevented ``fix`` from being used with a new model
(:issue:`156`).
- Added ``first_obs`` and ``last_obs`` parameters to ``fix`` to mimic ``fit``.
- Added ability to jointly estimate smoothing parameter in EWMA variance when
fitting the model.
- Added ability to pass optimization options to ARCH model estimation
(:issue:`195`).