Leave-one-out Statistic Influence

How to use Leave-one-out Statistic Influence

Recompute the chosen statistic after omitting each source observation. Retain exact deletion changes and bias formula; smooth summary modes also report the explicit jackknife variance and its approximate square root.

1. Use the example as the schema; replace its labels and entered model assumptions.
2. Recompute the chosen statistic after omitting each source observation. Retain exact deletion changes and bias formula; smooth summary modes also report the explicit jackknife variance and its approximate square root.
3. Calculate, inspect the complete witnesses and limitations, then copy or download the JSON report.

Good to know

• 3–200 decimal-string observations of magnitude at most 1,000,000,000 with six places. Mean, sample variance and median stay on this page; all deletions retain one-based source indices.
• Median variance and standard error are omitted because ordinary jackknife approximation can be poor for nonsmooth quantiles. No confidence coverage claim, automatic data deletion or inference about dependent samples.
• Local calculation with no upload, input persistence or outside lookup. Model JSON is limited to 30,000 characters and 10,000 values. Decimal quantities are strings with up to six places; count fields use plain JSON integers. Exact fractions are capped at 8,192 bits. The complete JSON output is limited to 1,000,000 characters; approximate numbers preserve their stored values. Unsupported states fail explicitly.