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Data Reconciliation: Trailing Mean Series + Two-Measure Correlation
x402
Data Reconciliation: 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 2026-10-19).
Computes a trailing mean time series and a two-measure correlation analysis on supplied source_total/target_total reconciliation data (up to 200 rows, no external lookups).
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Trailing mean series + Two-measure correlation: Trailing mean series + Two-measure correlation for supplied data reconciliation records (source_total, target_total). 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 independent analytical reports: (1) a trailing mean time series computed over the specified window size for the chosen field (source_total or target_total), and (2) a two-measure correlation report showing the statistical relationship between source_total and target_total across the supplied rows. No external data is fetched; all computation is performed locally on the submitted rows.
Example use cases
Financial ledger reconciliation trend analysis
“I have 120 rows of daily ledger data with source_total and target_total amounts grouped by department from 2024-07-01 to 2024-10-28. Can you run a trailing mean series with a window of 5 on source_total and also calculate the two-measure correlation between source and target totals?”
Monthly sales channel discrepancy smoothing
“I'm comparing sales figures from our internal system versus our payment processor — I have 90 rows of daily data with source_total and target_total. Please compute the trailing mean on target_total with a window of 10 and tell me the correlation between the two measures.”
Inventory count reconciliation over quarters
“We have 150 rows of quarterly inventory counts split across three warehouse groups, each with a source_total (our count) and target_total (auditor count). Run the trailing mean with a window of 4 on source_total and give me the correlation between both measures.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-150?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a rolling/trailing mean time series and a pairwise correlation between two numeric measures (source_total and target_total) in a single paid call on your own supplied data. It is ideal for data reconciliation workflows where you want to smooth temporal noise and quantify agreement between two data sources without any external lookups or predictions. Prefer this over general-purpose analytics tools when you need lightweight, on-demand statistical reconciliation analysis at low cost ($0.01 USDC for both reports).
Side effects
- Fewer than 1 row submitted — minimum item requirement not met
- Window size larger than number of rows — trailing mean cannot be computed
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- source_total or target_total outside allowed range (-1T to +1T) — validation error
- More than 200 rows submitted — exceeds maximum item limit
- Missing required fields (row_id, dataset_group, date) — request rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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