#272 added geometric averaging type to the Development() estimator

[kennethshsu]

Summary of Changes

Added geometric LDFs in the Development() estimator.

Related GitHub Issue(s)

• Fixes Medial and geometric averages #272
• Removed blocker for Reconcile data against Friedland's text used in Exam 5 #588

Additional Context for Reviewers

Because geometric averaging cannot be easily implemented in the regression framework, it is calculated outside. We then have to carefully nan out all relevant params related to the estimated values, such as sigma_, std_err_, and std_residuals_.

• I passed tests locally for both code (uv run pytest) and documentation changes (uv run jb build docs --builder=custom --custom-builder=doctest)

---

Note

Medium Risk
Introduces a new averaging mode and rewires weighted regression/std-error calculations, which can change LDFs and stochastic outputs (sigma_, std_err_, residuals) across workflows if behavior differs from prior methods.

Overview
Adds geometric averaging as a supported average option for Development, including per-development-period mixing of simple/geometric methods.

Refactors WeightedRegression to accept the chosen averaging method, compute regression weights internally (tracking _w_reg/exponent_), handle geometric averaging via a log-based coefficient calculation with a new warning for zero values, and centralizes std_err_ filling via a new std_err_fill() helper. Updates Development.fit() to use these new regression outputs when computing standardized residuals.

Expands the test suite to validate geometric/simple averaging results and to assert expected sigma_, std_err_, and std_residuals_ values.

^{Reviewed by Cursor Bugbot for commit 81cef7e. Bugbot is set up for automated code reviews on this repo. Configure here.}

[kennethshsu]

@henrydingliu ok ready for review!

[kennethshsu]

In case anyone wants to look at the Excel replication.
geomean.xlsx

[henrydingliu]

do we need any extra error catching around negative values ?

[kennethshsu]

I don't think a cumulative triangle can ever be negative. But I do a potential problem in an edge case where losses are 0 for the first few periods for a super long tailed business. In that case, the geometric LDFs will error out...

[henrydingliu]

geometric ldf is calculated regardless of whether it's selected, correct? so this could error out even when the user doesn't want geomean at all

[kennethshsu]

Yes, that's a good point, though not likely, but ya I can add a guard to skip if geometric is not present so it runs faster.

[cursor]

Cursor Bugbot has reviewed your changes and found 1 potential issue.

^{❌ Bugbot Autofix is OFF. To automatically fix reported issues with cloud agents, enable autofix in the Cursor dashboard.}

^{Reviewed by Cursor Bugbot for commit 2737959. Configure here.}

[henrydingliu]

harmonic mean next?

[kennethshsu]

lol if you have the formulas we can do it, it's been refactored so should be pretty easy