Description
Return one observation's multiplicity and share in supplied bootstrap draws.
Weights, hash collisions and regression diagnostics have estimator-specific meanings. A local count, signed contribution or residual scaling can be calculated from supplied inputs without establishing sampling validity or model quality.
Return one observation's multiplicity and share in supplied bootstrap draws.
When to use this tool
Use Bootstrap One Draw Multiplicity Term when checking the stated weight, hash or diagnostic contribution.
How to use the tool and how it works
- Enter draws, observation, sampleSize. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read multiplicity, weight. Use the output convention below.
Return one observation's multiplicity and share in supplied bootstrap draws. Require positive whole sampleSize, valid observation and in-range draw values; count equality and divide by draw-list length, or return zero for empty draws.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| draws | Supplied whole observation indices in [0,sampleSize); this tool does not generate random draws. | Required. Array of safe integer; maximum items 256. |
| observation | Observation | Required. Safe integer; minimum 0. |
| sampleSize | Sample Size | Required. Safe integer; minimum 1. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| multiplicity | Multiplicity | Required. Safe integer. |
| weight | Multiplicity divided by draws.length; zero for an empty draw list. | Required. Finite number. |
{
"input": {
"draws": [
0,
1,
1,
2
],
"observation": 1,
"sampleSize": 3
},
"output": {
"multiplicity": 2,
"weight": 0.5
}
}Limitations and assumptions
- Draws are supplied, not sampled; empty-draw weight is a convention rather than an inferred sampling probability.
- Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
- Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.
Alternative or Complementary methods
Use a complete estimator or feature pipeline and justified assumptions to assess statistical impact, uncertainty and model behavior.
References
Similar or alternative tools
- Sample Weight Clipping Mass Loss
Return clipped sample weight and its lost share of original total.
- Sample Weight Unknown Support Flag
Separate known and unknown sample-weight totals.