Releases: QuantEcon/QuantEcon.py
14th March 2024
What's Changed
- FIX: Update license file from BSD-3 to MIT by @mmcky in #712
- MAINT: Update end year in License by @mmcky in #713
- Add citation by @Smit-create in #719
- Update ci.yml to latest version by @kp992 in #718
- FIX: linprog_simplex: Fix bug in Phase 1 by @oyamad in #727
- RELEASE v.0.7.2 by @mmcky in #728
New Contributors
Full Changelog: v0.7.1...v0.7.2
JOSS PAPER: 06th December 2023
This release is to support the JOSS paper.
JOSS PAPER: 04th December 2023
This release is to support the JOSS
paper.
v0.7.1
Ver 0.7.1 (29-May-2023)
This is a minor release with bug fixes and improvements to documentation.
Fix
Thank you to oyamad, HengchengZhang for your contributions
v0.7.0
Ver 0.7.0 (24-April-2023)
New
- END: Add function fit_discrete_mc (jstac), (Smit-create) and (oyamad) which takes a time series and fits a finite markov chain
- ENH: Adding Discrete Approximation of VAR Methods (crondonm)
- ENH: Implement LCP solver (oyamad)
Fixes and Maintenance
There were a range of additional maitenance and fixes including
RFC: Replace @generated_jit
with @overload
,
Update __Iss.py - Remove broken link,
FIX: Add __dir__
to lss.py,
MAINT: Rename ivy.py to ivp.py,
Bring estimate_mc into top level namespace,
Warn only when n in not int in tauchen,
FIX: Avoid bare 'except',
FIX: DOC: Remove 2-byte spaces
Thank you to (bensonarafat), (crondonm), (oyamad), (jstac), and (Smit-create) for all your contributions, PR reviews, and comments.
v0.6.0
Ver 0.6.0 (18-December-2022)
This is the next major release of the quantecon
package as it includes some breaking changes as listed below. It also
includes a number of new features and enhancements including learning algorithms in the game theory module, MLE estimation
for Markov Chains, in addition to some useful helper functions.
PR #601: Updates to public and private API
includes some deprecations which will issue warnings and a helpful suggestion on how to
update any effected imports from the quantecon
package.
Breaking
New
- ENH: Add MLE Estimation for Markov Chains (jstac)
- ENH: Implement cartesian_nearest_index (oyamad)
- ENH: check_random_state: Accept np.random.Generator (oyamad)
- ENH: Add learning algorithms to Game Theory module (Yuya-Furusawa)
Fixes
- FIX: Fix dtype in cartesian (oyamad)
- FIX: Bugfix in brd.py (oyamad)
- MAINT: player.is_dominated: Allow recent methods for scipy.optimize.linprog (oyamad)
- MAINT: Distinguish between private and public namespaces (Smit-create).
- MAINT: Clairfy hamilton_filter API (rht)
Thank you to (oyamad), (jstac), (Smit-create),
(rht), and (Yuya-Furusawa) for all your contributions, PR reviews, and comments.
v0.5.3
Ver 0.5.3 (07-April-2022)
This is primarily a maintenance release to fix a number of deprecation notices, migrating the tests to use pytest
rather than nose
, and python packaging is moving to flit
Enhancement:
Thanks Smit-create as a first time contributor to the project, and oyamad for your assistance with this release.
Release of version 0.5.2
Ver 0.5.2 (16-November-2021)
This is a bug fix release
Maintain:
- FIX: markov: Respect dtype of P in cdfs ([oyamad], thanks @btanner for reporting issue)
- LGTM code quality suggestions (nshea3)
Release of version 0.5.1
Ver 0.5.1 (27-June-2021)
New:
- ENH: Add Numba-jitted linprog solver ([oyamad])
- EHN: Add minmax solver ([oyamad])
- ENH: Add LP solution method to DiscreteDP ([oyamad])
Maintain:
- MAINT: Use multivariate_normal via random_state ([oyamad])
- FIX: minmax: Fix redundancy ([oyamad])
- DOCS: Fix typos in Docs ([timgates42])
thanks @oyamad and @timgates42
Release of version 0.5.0
Ver 0.5.0 (19-April-2021)
Breaking Changes:
Other Changes:
- FIX: [kalman] Always initialize self.Sigma and self.x_hat #562 (rht)
- TST: Setup Tests via Github Actions #561 (rht)
- ENH: Update root_finding.py #560 (alanlujan91)
Special thanks for contributions by rht, shizejin, alanlujan91, and oyamad