Description
Test whether quantile lies within a supplied cumulative interval: before<quantile<=after with includeEquality, otherwise before<=quantile<after.
A statistical term depends on its data summaries, weighting convention, centering, denominator, and boundary rules. A contribution, derivative, domain check, or converted summary answers a narrower question than a complete estimator. Those conventions must match before terms are combined or compared.
Test whether quantile lies within a supplied cumulative interval: before<quantile<=after with includeEquality, otherwise before<=quantile<after.
When to use this tool
Use Weighted Quantile Cumulative Boundary Choice when you need this specific summary conversion, contribution, domain rule, or sensitivity term with matching statistical conventions.
How to use the tool and how it works
- Enter before, after, quantile, includeEquality. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read selected. Inspect selected before interpreting the associated values.
Test whether quantile lies within a supplied cumulative interval: before<quantile<=after with includeEquality, otherwise before<=quantile<after. Require all three fractions within zero through one and before<=after.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| before | Before | Required. Finite number; minimum 0; maximum 1. |
| after | After | Required. Finite number; minimum 0; maximum 1. |
| quantile | Quantile | Required. Finite number; minimum 0; maximum 1. |
| includeEquality | Selects (before,after] when true or [before,after) otherwise. | Required. Boolean. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| selected | Selected | Required. Boolean. |
{
"input": {
"before": 0.25,
"after": 0.5,
"quantile": 0.5,
"includeEquality": true
},
"output": {
"selected": true
}
}Limitations and assumptions
- IncludeEquality selects which endpoint owns a boundary. This does not compute a weighted quantile, establish a probability distribution, or infer interpolation conventions.
- The field tables state structural bounds; the mechanics also specify cross-field constraints. Malformed inputs and unsupported domains cause errors. A successful false flag, empty branch value, or zero placeholder has the meaning stated above and is distinct from an input error.
- 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. Signed zero is exported as zero.
Alternative or Complementary methods
Use a complete estimator or model when a contribution, sensitivity, or domain check is insufficient. Verify the weight semantics, centering, denominator, and sampling assumptions before combining summaries.
References
Similar or alternative tools
- Weighted Quantile Atom Boundary
Weighted empirical inverse using an explicit >= versus > atom-boundary convention, clamped at probability one.
- Histogram Bin Boundary Roundoff Policy
Classify value below or above edge, treating values within inclusive absolute tolerance as snapped and assigning them according to preferUpper.