Description
Return defined only when both supplied variances are positive, with constantFirst and constantSecond for exact zero variances.
A similarity term depends on the comparison universe, missing-value policy, treatment of repeated features, and normalization. A score can also have a caller-selected value when its mathematical denominator vanishes. Those conventions matter before interpreting a threshold or comparing methods.
Return defined only when both supplied variances are positive, with constantFirst and constantSecond for exact zero variances.
When to use this tool
Use Pearson Similarity Constant Input Domain when you need this particular comparison term, normalization, domain condition, or empty-result policy in a larger matching workflow.
How to use the tool and how it works
- Enter firstVariance, secondVariance. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read defined, constantFirst, constantSecond. Inspect defined, constantFirst, constantSecond before interpreting the associated values.
Return defined only when both supplied variances are positive, with constantFirst and constantSecond for exact zero variances. Require nonnegative variances.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| firstVariance | First Variance | Required. Finite number; minimum 0. |
| secondVariance | Second Variance | Required. Finite number; minimum 0. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| defined | Whether the stated denominator or quantity is defined; inspect before interpreting a placeholder. | Required. Boolean. |
| constantFirst | Constant First | Required. Boolean. |
| constantSecond | Constant Second | Required. Boolean. |
{
"input": {
"firstVariance": 0,
"secondVariance": 2
},
"output": {
"defined": false,
"constantFirst": true,
"constantSecond": false
}
}Limitations and assumptions
- No correlation is calculated or estimated. The flags trust the supplied summaries and do not verify whether actual feature sequences are constant or statistically comparable.
- 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
Compare methods only after aligning feature definitions, missingness, empty policies, multiplicities, and normalizers. Use a complete comparison when the tool returns only one contribution or count check.
References
Similar or alternative tools
- Edit Similarity Missing Versus Empty Label
Return comparable when neither missing flag is true and bothEmpty only for two comparable empty strings.
- Hamming Similarity Length Mismatch Policy
Normalize mismatches by the greater length, adding the length difference as errors only when padMissing.