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Forecast Verification IQR Outlier Flags + Secondary-Measure Weighted Mean
x402
Forecast Verification IQR Outlier Flags + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).
Computes IQR-based outlier flags and secondary-measure weighted mean statistics on up to 200 rows of forecast vs. observed value pairs.
Price / call$0.01
Success—
StatusUnknown
How this service works
Forecast verification inputs — IQR outlier flags + Secondary-measure weighted mean: IQR outlier flags + Secondary-measure weighted mean for supplied forecast verification inputs records (forecast_value, observed_value). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two analytical reports on the submitted rows: (1) IQR-based outlier flags indicating which rows have forecast or observed values outside the interquartile range, and (2) a secondary-measure weighted mean summarizing the numeric field across the dataset. No external data is fetched; all analysis is performed locally on the supplied rows.
Example use cases
Detect outlier forecasts in weather data
“I have a batch of daily weather forecast vs. observed temperature records for two station groups from last month — can you flag which forecast_value entries are IQR outliers and give me the secondary-measure weighted mean across up to 50 rows?”
Forecast accuracy audit for model evaluation
“I'm evaluating a forecast model and need to know which of my 120 forecast-observation pairs have outlier forecast values according to IQR rules, plus the weighted mean of the observed_value field as a secondary measure — can you run those two reports?”
Station group anomaly check after storm event
“After last week's storm, I need to check my forecast verification records for station groups A and B — please flag any IQR outliers in the observed_value column and compute the weighted mean for the secondary measure across my 80 rows.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-24-177?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of paired forecast and observed numeric values and need both IQR outlier detection and weighted mean statistics in a single call, without requiring any live data lookup or external prediction. Ideal for batch forecast verification audits, model evaluation pipelines, and data quality checks on weather or similar time-series forecast data.
Side effects
- Fewer than 1 row submitted — request rejected
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, forecast_value, observed_value) — validation error
- Invalid date format not matching YYYY-MM-DD — schema validation failure
- Non-numeric values in forecast_value or observed_value — computation error
- Payment of 0.01 USDC not completed — 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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