chainladder 0.7.8

Bug Fixes

• Resolved #87 val_to_dev with malformed triangle

Enhancements

• Major overhaul of Triangle internals for better code clarity and more efficiency
• Made sparse operations more efficient for larger triangles
• to_frame now works on Triangles that are 3D or 4D. For example clrd.to_frame()
• Advanced groupby operations supported. For (trivial) example:

clrd = cl.load_sample('clrd')
# Split companies with names less than 15 characters vs those above: 
clrd.groupby(clrd.index['GRNAME'].str.len()<15).sum()

chainladder 0.7.7

Enhancements

• #97, loc and iloc now support Ellipsis
• Development can now take a float value for averaging. When float value is used, it corresponds to weight exponent (delta in Barnett/Zenwirth). Only special cases had previously existed - {"regression": 0.0, "volume": 1.0, "simple": 2.0}
• Major improvements in slicing performance.

Bug fixes

• #96, Fix for TailBase transform
• #94, n_periods with asymmetric triangles fixed

chainladder 0.7.6

Enhancements

• Four Dimensional slicing is now supported.

clrd = cl.load_sample('clrd')
clrd.iloc[[0,10, 3], 1:8, :5, :]
clrd.loc[:'Aegis Grp', 'CumPaidLoss':, '1990':'1994', :48]

• #92 to_frame() now takes optional origin_as_datetime argument for better compatibility with various plotting libraries (Thank you @johalnes )

tri.to_frame(origin_as_datetime=True)

Bug Fixes

• Patches to the interaction between sparse and numpy arrays to accomodate more scenarios.
• Patches to multi-index broadcasting
• Improved performance of latest_diagonal for sparse backends
• #91 Bug fix to MackChainladder which errored on asymmetric triangles (Thank you @johalnes for reporting)

chainladder 0.7.5

Enhancements

• Enabled multi-index broadcasting.

clrd = cl.load_sample('clrd')
clrd / clrd.groupby('LOB').sum()  # LOB alignment works now instead of throwing error

• Added sparse representation of triangles which substantially increases the size limit of in-memory triangles. Check out the new Large Datasets tutorial for details

Bug fixes

• Fixed cupy backend which had previously been neglected
• Fixed xlcompose issue where Period fails when included as column header

chainladder 0.7.4

Tiny release.

Bug Fixes:

• Fixed a bug where Triangle did not support full accident dates at creation
• Fixed an inappropriate index mutation in Triangle index

Enhancements

• Added head and tail methods to Triangle
• Prepped Triangle class to support sparse backend
• Added prism sample dataset for sparse demonstrations and unit tests

chainladder 0.7.3

Enhancements

• Improved performance of valuation axis
• Improved performance of groupby
• Added sort_index method to Triangle consistent with pandas
• Allow for fit_predict to be called on a Pipeline estimator

Bug fixes

• Fixed issue with Bootstrap process variance where it was being applied more than once
• Fixed but where Triangle.index did not ingest numeric columns appropriately.

chainladder 0.7.2

Bug fixes:

• Index slicing not compatible with pandas #84 fixed
• arithmetic fail #68 - Substantial reworking of how arithmetic works.
• JSON IO on sub-triangles now works
• predict and fit_predict methods added to all IBNR models and now function as expected

Enhancements:

• Allow DevelopmentConstant to take on more than one set of patterns by passing in a callable
• MunichAdjustmentAllow ` does not work when P/I or I/P ratios cannot be calculated. You can now optionally back-fill zero values with expectaton from simple chainladder so that Munich can be performed on sparser triangles.

Refactors:

• Performance optimized several triangle functions including slicing and val_to_dev
• Reduced footprint of ldf_, sigma, and std_err_ triangles
• Standardized IBNR model methods
• Changed cdf_, full_triangle_, full_expectation_, ibnr_ to function-based properties instead of in-memory objects to reduce memory footprint

chainladder 0.7.1

Enhancements

• Added heatmap method to Triangle - allows for conditionally formatting a 2D triangle. Useful for detecting link_ratio outliers
• Introduced BerquistSherman estimator
• Better error messaging when triangle columns are non-numeric
• Broadened the functionality of Triangle.trend
• Allow for nested estimators in to_json. Required addition for the new BerquistSherman method
• Docs, docs, and more docs.

Bug Fixes

• Mixed an inappropriate mutation in MunichAdjustment.transform
• Triangle column slicing now supports pd.Index objects instead of just lists

Other

• Moved BootstrapODPSample to workflow section as it is not a development estimator.

chainladder 0.7.0

Bug fixes

• TailBondy now works with multiple (4D) triangles
• TailBondy computes correctly when earliest_age is selected
• Sub-triangles now honor index and column slicing of the parent.
• fit_transform for all tail estimators now correctly propagate all estimator attributes
• Bondy decay now uses the generalized Bondy formula instead of exponential decay

Enhancements

• Every tail estimator now has a tail_ attribute representing the point estimate of the tail
• Every tail estimator how has an attachment_age parameter to allow for attachment before the end of the triangle
• TailCurve now has slope_ and intercept_ attributes for a diagnostics of the estimator.
• TailBondy now has earliest_ldf_ attributes to allow for diagnostics of the estimator.
• Substantial improvement to the documents on Tails.
• Introduced the deterministic components of ClarkLDF and TailClark estimators to allow for growth curve selection of development patterns.

chainladder 0.6.3

Enhancements (courtesy of @gig67):

• Added Triangle.calendar_correlation method and companion class CalendarCorrelation to support detecting calendar year correlations in triangles.
• Added Triangle.developmen_correlation method and companion class DevelopmentCorrelation to support detecting development correlations in triangles.