Description
For nonnegative sumSquares and integer 0<=missing<=count set denominator=count-missing minus one if sample.
Normalization depends on the supplied center, scale, norm, range, reference distribution, or denominator. A zero spread and a missing denominator need an explicit policy, and clipping differs from fitting a scaler. Evaluating one scalar or derivative term does not estimate every parameter or establish a distributional improvement.
For nonnegative sumSquares and integer 0<=missing<=count set denominator=count-missing minus one if sample.
When to use this tool
Use Row Standardization One Missing Denominator when you already have the required normalization parameters and need this local scalar, range, policy, or derivative term.
How to use the tool and how it works
- Enter sumSquares, count, missing, sample. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read denominator, defined, variance. Inspect defined before interpreting the associated values.
For nonnegative sumSquares and integer 0<=missing<=count set denominator=count-missing minus one if sample. Return defined when denominator>0 and variance=sumSquares/denominator when defined, otherwise zero.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| sumSquares | Already-centered squared-deviation sum for retained observations, in data units squared. | Required. Finite number; minimum 0. |
| count | Total count including missing entries. | Required. Safe integer; minimum 0. |
| missing | Missing | Required. Safe integer; minimum 0. |
| sample | Sample | Required. Boolean. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| denominator | Retained count minus one if sample; may be zero or negative. | Required. Safe integer. |
| defined | Whether the stated denominator or quantity is defined; inspect before using a placeholder. | Required. Boolean. |
| variance | Positive supplied variance in squared residual units, or returned variance under the stated branch. | Required. Finite number. |
{
"input": {
"sumSquares": 12,
"count": 5,
"missing": 1,
"sample": true
},
"output": {
"denominator": 3,
"defined": true,
"variance": 4
}
}Limitations and assumptions
- SumSquares must already be the sum of squared centered deviations for the retained observations, in data units squared. The tool does not subtract a mean or reconstruct missing observations; zero on a nonpositive denominator is a placeholder, not measured zero variance.
- 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
Fit or verify the intended scaler parameters and statistical model separately. Check units, zero policies, missingness, clipping, inverse conventions, and whether supplied norms or denominators belong to the same data.
References
Similar or alternative tools
- Standardized Residual Reference Variance Pair
For positive variance return standardized=residual/sqrt(variance) and squared=standardized^2.
- Normalization: Robust Scaler Zero Spread Policy
Compute one robust-reference normalized scalar with an explicit reject/zero policy for a supplied zero spread, preserving defined status.