Description
Calculate one scalar squared weighted-score contribution for a robust-covariance calculation.
Econometric calculations separate supplied residuals, regressors, weights, restrictions, panel groups and reference periods. One score or moment contribution is not a fitted estimator, and one scalar covariance term is not a standard error. Unit rescaling and event-time arithmetic preserve conventions without establishing model identification or causal interpretation.
Calculate one scalar squared weighted-score contribution for a robust-covariance calculation.
When to use this tool
Use Heteroskedasticity Robust Meat Row when you already have regressor, residual, analyticWeight and need to calculate one scalar squared weighted-score contribution for a robust-covariance calculation.
How to use the tool and how it works
- Enter regressor, residual, analyticWeight. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read scalarMeatContribution. Use the output convention below.
Require analyticWeight>=0; return (analyticWeight*regressor*residual)^2.1
Heteroskedasticity-consistent parameter uncertainty requires a complete covariance estimator. A single squared score term, with the caller's specified weight, does not produce that estimator or its standard errors.2
| Input field | Meaning and units | Accepted input |
|---|---|---|
| regressor | Regressor | Required. Finite number. |
| residual | Residual | Required. Finite number. |
| analyticWeight | Analytic Weight | Required. Finite number; minimum 0. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| scalarMeatContribution | (analyticWeight*regressor*residual)^2, including the square of the supplied weight; not a full covariance. | Required. Finite number. |
{
"input": {
"regressor": 2,
"residual": 3,
"analyticWeight": 0.5
},
"output": {
"scalarMeatContribution": 9
}
}Limitations and assumptions
- This uses the square of the supplied weight, not a single weight factor. It is one scalar meat term, not the bread, covariance matrix, finite-sample correction, clustered estimate or standard error.
- 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 and evaluate the full specified model with appropriate data, grouping and uncertainty treatment for inference. Aggregate the required score/moment terms and use the complete covariance calculation; a local residual, cutoff flag or supplied coefficient transformation does not validate the estimator.
References
Similar or alternative tools
- Weighted Regression Single Score Term
Calculate one weighted regression score contribution.
- Clustered Score Single Observation Contribution
Label one supplied regression-score contribution by cluster.