Parous Rate Survival Daily Proportion p Calculator
Invert the stationary parity model p=P^(1/g); parity is not itself a directly observed daily survival probability.
Description
Invert the stationary parity model p=P^(1/g); parity is not itself a directly observed daily survival probability.
A parity-based survival estimate is conditional on a stationary model connecting the parous fraction with cycle duration. The assumption belongs with the reported daily probability.
When to use this tool
Invert the stationary parity model p=P^(1/g); parity is not itself a directly observed daily survival probability.
- Prepare the supplied parousFraction, cycleDays fields for this operation.
- Compare the complete example with the representation used by your own input before carrying the result into another step.
How to use the tool and how it works
- Enter parousFraction, cycleDays. Use the exact text syntax, units and index conventions explained below.
- Run the tool. If input validation fails, correct the supplied fields before interpreting any result.
- Read result.conditionalDailySurvival, result.assumption. Interpret false, null and empty lists using the distinctions below; they can be valid outputs.
Require parousFraction within zero through one and positive cycleDays. Return parousFraction raised to 1/cycleDays as conditionalDailySurvival and the stationary-parity-model label.1
| Input field | Meaning and representation | Accepted input |
|---|---|---|
| parousFraction | parous fraction. | Finite number; from zero through one inclusive |
| cycleDays | cycle days. | Finite number; greater than zero |
| Output field | Interpretation |
|---|---|
| result | Object containing the named outputs below. |
| result.conditionalDailySurvival | The conditional daily survival value under the stated formula or text convention. |
| result.assumption | The assumption value under the stated formula or text convention. |
{
"input": {
"parousFraction": 0.25,
"cycleDays": 2
},
"output": {
"result": {
"conditionalDailySurvival": 0.5,
"assumption": "stationary-parity-model"
}
}
}Limitations and assumptions
- The tool does not measure survival, validate stationarity or account for varying cycle lengths. Inputs at zero and one give boundary probabilities; no confidence interval is estimated.
- Every declared top-level field is required and unexpected fields are rejected. Numeric inputs must be finite; ordinary text fields are bounded to 8,192 UTF-16 code units, with tighter operation-specific limits where stated.
- Ordinary string lists have at most 128 entries of at most 128 code units each; numeric lists and matrices have separate bounded size checks. Nonfinite results and excessively large serialized outputs are rejected.
- Indexes are zero-based and spans have an exclusive end unless explicitly stated otherwise. A valid false, null or empty-list result is distinct from malformed input.
Alternative or Complementary methods
Combine recorded observations with a validated method, appropriate controls and the complete specimen context. Use original qualified references when reviewing species, stages or product information; a supplied-record match, sample ratio or historical flag is only the stated piece of evidence.
References
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