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Record Routing Analytics: Trailing Mean Series + Two-Measure Correlation
x402
Record Routing Analytics: Trailing Mean Series + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Computes a trailing mean time series and a two-measure Pearson/correlation analysis for accepted_records and rejected_records data supplied by the caller, using local analytical engines with no external lookups.
Price / call$0.01
Success—
StatusUnknown
How this service works
Record routing — Trailing mean series + Two-measure correlation: Trailing mean series + Two-measure correlation for supplied record routing records (accepted_records, rejected_records). 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: (1) a trailing mean time series for the chosen field (accepted_records or rejected_records) computed over the specified rolling window across up to 200 rows, and (2) a two-measure correlation report quantifying the statistical relationship between accepted_records and rejected_records. All computation is performed locally with no external data fetching.
Example use cases
Data pipeline acceptance rate trend
“I have daily record routing logs for the past month with accepted and rejected counts per group — can you compute a trailing mean series with a window of 7 over accepted_records so I can see the smoothed acceptance trend?”
Correlation between accepted and rejected records
“For this dataset of 50 record routing rows across two groups, I want to know how strongly accepted_records and rejected_records correlate with each other — run the two-measure correlation report for me.”
Detect anomalies in rejection spikes
“I've got 120 rows of daily record routing data split across three dataset groups — run a trailing mean analysis with a window of 5 on rejected_records so I can spot where rejection rates deviate from the rolling baseline.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-19-150?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of record routing data (with accepted and rejected counts) and need both a rolling/trailing mean time series AND a correlation analysis between the two measures in a single low-cost call ($0.01 USDC). Prefer it over generic statistics APIs when your data fits the accepted_records/rejected_records schema and you want two bundled analytical reports without external data dependencies or live lookups.
Side effects
- Fewer than 1 row provided — rejected with validation error
- Window size larger than number of rows — may produce empty or sparse trailing mean output
- Null values in accepted_records or rejected_records — may reduce effective row count for correlation
- Invalid date format not matching YYYY-MM-DD — schema validation failure
- More than 200 rows submitted — request rejected, maxItems exceeded
- Invalid field enum value — schema validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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