ltriangle robustness: finite starting values, bounded-support tests, docs - #183
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joethorley merged 2 commits intoJul 14, 2026
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…nded-support tests and docs Follow-up to #169. - sltriangle() falls back to a small positive half-width when the data have no spread on the log scale, avoiding a -Inf starting value. - Add tests that ssd_hc()/predict() are finite and monotonic across the full 1-99% range for the bounded-support distribution. - Note in the distributions vignette that ltriangle is experimental and not part of the default BCANZ set. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Follow-up to #169 (targets the
add-triangle-distributionbranch).Addresses the non-behavior-changing review items from the #169 review:
sltriangle()starting values. When the data have no spread on the log scale (e.g. all concentrations equal),max(abs(logx - location))is 0 andlog_scalelogbecame-Inf. It now falls back to a small positive half-width so the starting value stays finite. Fits on data with spread are unchanged.ssd_hc()andpredict()return finite, monotonic estimates across the full 1-99% range.ltriangleis experimental and not part of the default BCANZ set (ssd_dists_bcanz()), so it is only fitted when explicitly requested.No change to fitted results for normal data, so no fit-value snapshots change.
The relative-density-floor change (the statistical item from the review) is handled separately in a companion PR so the likelihood change and its snapshot updates can be reviewed on their own.
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