chainladder 0.8.13

The majority of this release was written by @kennethshsu and contains a first-time contribution from @genedan. Thank you!

Bug Fixes:

• #270 Fixed an issue affecting triangle instantiation
• #251 Fixed a bug in predict method that failed to honor development ages appropriatly
• #274 Addressed a pandas deprecation notice in the heatmap method.
• #258 Addressed silent error when predicting on a Triangle that is larger than the underlying model.
• #288 Addressed Bug in to_frame method
• #283 Addressed Bug in the calculation of LDFs in CaseOutstanding

Enhancements

• #293 Expanded functionality drop_high and drop_low arguments of Development estimator.
• #298, #299, #304, #305, #308 Documentation clean-up.

chainladder 0.8.12

Bug Fixes:

• #254 Fixed an undesired mutation when using cl.concat
• #257 to_frame bug fix on empty triangles
• #248 to_frame bug and deprecation notice in origin_as_datetime argument.
• #250 Bug fix in triangle initialization
• #258 Addressed silent error when predicting on a Triangle that is larger than the underlying model.
• #261 Addressed a pandas>1.4.0 bug

Enhancements

Introduced ExpectedLoss method

• #242 Added threshold based dropping of link ratios to Development estimator
• #158 Triangles can now be instantiated with only one data point.
• #250 python 3.10 support
• #260 fillna method added to Triangle class that supports filling with constants or other Triangles.
• Support for 'H' or 'S' when using half year grain

chainladder 0.8.11-beta

v0.8.11-beta

prep 0.8.11 release

chainladder 0.8.11-alpha

Bug Fixes:

• #239 val_to_dev bug fixed
• #254 Fixed an undesired mutation when using cl.concat
• #257 to_frame bug fix on empty triangles
• #248 to_frame bug and deprecation notice in origin_as_datetime argument.
• #250 Bug fix in triangle initialization
• #258 Addressed silent error when predicting on a Triangle that is larger than the underlying model.
• #261 Addressed a pandas>1.4.0 bug

Enhancements

• Introduced ExpectedLoss method
• #242 Added threshold based dropping of link ratios to Development estimator
• #158 Triangles can now be instantiated with only one data point.
• #250 python 3.10 support
• #260 fillna method added to Triangle class that supports filling with constants or other Triangles.

chainladder 0.8.10

Enhancements

• #225 - Added support for mid-year triangles
• Remove xlcompose as a dependency
• #233 and #219 - Added more explicit warning when is_cumulative property of triangle is not set.
• #192 Expanded drop_high and drop_low functionality to include integers and variable length lists. PR courtesy of @kennethshsu.

Bug fixes

• #234 Coerce MackChainladder to zero variance when inbr_ and cdf_ are 0.
• Fix bug in BarnettZehnwirth.transform that was previously not applying the log-transform correctly

chainladder 0.8.9

Enhancements

• #198 Added projection_period to all Tail estimators. This allows for analyzing run-off beyond a one year time horizon.
• #214 A refreshed docs theme using jupyter-book!
• #200 Added more flexibility to TailCurve.fit_period to allow boolean lists - similar to Development.drop_high
• @kennethshsu further improved tutorials

Bug Fixes

• #210 Fixed regression in triangle instantiation where grain=='S' is being interpreted as seconds and not semesters.
• #213 Fixed an unintended Triangle mutation when reassigning columns on a sparse backend.
• #221 Fixed origin/development broadcasting issue that was causing silent bugs in calculations on malformed triangles.

chainladder 0.8.8

Enhancements

• #140 Improved test coverage
• #126 Relaxed BootstrapODPSample column restriction
• #207 Improved tutorials

Bug Fixes

• #204 Fixed regression in grain
• #203 Fixed regression in slice
• Fixed regression in Benktander index broadcasting
• #205 Fixed CI/CD build

chainladder 0.8.7

Minor release to fix some chainladder==0.8.6 regressions.

Bug Fixes

• Fixed #190 - 0 values getting into heatmap
• Fixed #191 regression that didn't support earlier versions of pandas
• Fixed #197 Index broadcasting edge case
• Fixed valuation_date regression when instantiating Triangles as vectors

Enhancements

• #99 Added Semester as an additional grain
• Added parallel support to GridSearch using n_jobs argument
• More tutorial improvements from @kennethshsu

chainladder 0.8.6

Ehancements

• @kennethshsu improved heatmap shading
• Support for numpy reductions, e.g. np.sum(cl.load_sample('raa'))
• @kennethshsu further improved tutorials

Bug fixes

• #186 Fix bug that disallowed instantiating a full triangles
• #180 Fix bug that mutated original DataFrame when instantiating Triangle
• #182 Eliminate new deprecations warnings from pandas>=1.3
• #183 Better alignment with pandas on index broadcasting
• #179 Fixed nan befavior on val_to_dev
• implement TriangleGroupby.__getitem__ to support column selection on groupby operations to align with pandas, e.g. cl.load_sample('clrd').groupby('LOB')['CumPaidLoss']

chainladder 0.8.5

Enhancements

• #154 - Added groupby hyperparameter to several more estimators including the widely used Development estimator. This allows fitting development patterns at a higher grain than the Triangle all within the estiamtor or Pipeline.
• Improved index broadcasting for sparse arrays. Prior to 0.8.5, this code would
  inappropriately consume too much memory

prism = cl.load_sample('prism') 
prism / prism.groupby('Line').sum()

• Arithmetic label matching improved for all axes to align more with pandas
• Added model_diagnostics utility function to be used on fitted estimators.
• Initial support for dask arrays. Current support is basic, but will eventually allow for distributed computations on massive triangles.
• added numpy array protocol support to the Triangle class. Now numpy functions can be called on Triangles. For example:

np.sin(cl.load_sample('raa'))

• #169 - Made Triangle tutorial more beginner friendly - courtesy of @Kennethhsu

Bug fixes

• Better Estimator pickling support when callables are included in estimators.
• Minor bug fix in grain estimator.