Description
Require actualValue nonzero and return abs((linearizedValue - actualValue)/actualValue).
An interpolation weight, geometric extrapolation distance, and mathematical error bound describe different quantities. A curvature-based bound needs assumptions about the underlying function, not just a computed coordinate.
Require actualValue nonzero and return abs((linearizedValue - actualValue)/actualValue).
When to use this tool
Use Linearization Relative Error when you need one explicit interpolation error or amplification component.
How to use the tool and how it works
- Enter actualValue, linearizedValue. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read absoluteRelativeError. Use the output convention below.
Require actualValue nonzero and return abs((linearizedValue - actualValue)/actualValue).1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| actualValue | Actual Value | Required. Finite number. |
| linearizedValue | Linearized Value | Required. Finite number. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| absoluteRelativeError | Absolute Relative Error | Required. Finite number. |
{
"input": {
"actualValue": 8,
"linearizedValue": 10
},
"output": {
"absoluteRelativeError": 0.25
}
}Limitations and assumptions
- Output is a fraction, not percent; this compares supplied numbers without deriving a linearization, checking its domain, or certifying an error bound.
- 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
Establish valid derivative bounds and compare methods or measurements before claiming a prediction-error guarantee.
References
Similar or alternative tools
- Proportional Offset From Baseline
Multiply baseline by relativeOffset for offset and by 1 + relativeOffset for adjusted.
- Mean Error From Signed Sum
Divide signedErrorSum by positive integer observationCount for meanError.