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Fix/stats exact quantiles - #168
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Expected values follow numpy/pandas default linear interpolation (type 7). Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
t-digest (compression 100) gave badly wrong quartiles for small samples, e.g. median([1,100]) = 100. Replace it with an exact accumulator that stores non-missing values in a primitive array, sorts once, and uses linear interpolation (Hyndman-Fan type 7, the numpy/pandas default). Drop the now-unused com.tdunning:t-digest dependency. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Exact quantiles need every value, so numericSummary on an Iterator held O(n) doubles per numeric column. QuantileSketch now buffers up to 1000 values (exact, type 7 interpolation) and on the 1001st flushes them into a t-digest (compression 200) and streams from then on. min and max stay exact. Restores the t-digest dependency. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
…iles Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
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