Releases: scikit-hep/resample
Releases · scikit-hep/resample
v1.6.0rc3
another attempt to fix authors
v1.6.0rc2
fix authors
v1.6.0rc1
fix classifiers
v1.6.0rc0: Fix build (#169)
Modernize and fix build
v1.5.3 (Zenodo release)
No code change, this release is created to trigger Zenodo.
v1.5.2
What's Changed
- Update ci skripts and fix types #154
- bootstrap.resample now works with method="extended" when input is multi-dimensional #153
Full Changelog: v1.5.1...v1.5.2
v1.5.1
installation instructions in readme
v1.5.0
v1.5.0-beta
Pre-release for the upcoming v1.5.0 release
First full-featured release for general production use
1.0.1 (August 23, 2020)
- Minor fix to allow building from source.
1.0.0 (August 22, 2020)
API Changes
- Bootstrap and jackknife generators
resample.bootstrap.resample
andresample.jackknife.resample
are now exposed to compute replicates lazily. - Jackknife functions have been split into their own namespace
resample.jackknife
. - Empirical distribution helper functions moved to a
resample.empirical
namespace. - Random number seeding is now done through using
numpy
generators rather than a global random state. As a result the minimumnumpy
version is now 1.17. - Parametric bootstrap now estimates both parameters of the t distribution.
- Default confidence interval method changed from
"percentile"
to"bca"
. - Empirical quantile function no longer performs interpolation between quantiles.
Enhancements
- Added bootstrap estimate of bias.
- Added
bias_corrected
function for jackknife and bootstrap, which computes the bias corrected estimates. - Performance of jackknife computation was increased.
Bug fixes
- Removed incorrect implementation of Studentized bootstrap.
Deprecations
- Smoothing of bootstrap samples is no longer supported.
- Supremum norm and MISE functionals removed.
Other
- Benchmarks were added to track and compare performance of bootstrap and jackknife methods.