# Time Series Completeness — Trailing Mean + Two-Measure Correlation

> Time Series Completeness — Trailing Mean + 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 2026-10-15).

Computes a trailing mean series and a two-measure Pearson correlation for time series completeness records (observed_points vs expected_points) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-150?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/time-series-completeness-trailing-mean-two-measure-correlation-465e3b27
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_5UlGDTD4o7pyQ83fSCkbQ

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability time-series-completeness-trailing-mean-two-measure-correlation-465e3b27 -d '<json body>'
```

Example prompt: Run a trailing mean series and two-measure correlation on my time series completeness data — I have 120 rows with observed_points and expected_points per date for two dataset groups, using a window of 7 days on the observed_points field.

## When to prefer this

Choose this endpoint when you need both a smoothed trailing mean series and a correlation analysis on time series completeness data (observed vs expected points) in a single call. It is ideal for data quality monitoring workflows where you want to quantify data collection gaps and measure how closely observed volumes track expected volumes over time, without needing external data enrichment or live predictions.

## Known failure modes

- Fewer than 1 row supplied — validation error
- More than 200 rows submitted — exceeds maximum and will be rejected
- Window size larger than the number of rows — insufficient data for trailing mean
- Missing required fields (row_id, date, observed_points, expected_points) — schema validation failure
- Malformed date strings (not YYYY-MM-DD) — pattern validation error
- All null values in a measure — correlation computation undefined

## How this service works

Time series completeness — Trailing mean series + Two-measure correlation: Trailing mean series + Two-measure correlation for supplied time series completeness records (observed_points, expected_points). 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 series smoothed over the specified window for the chosen field (observed_points or expected_points), and (2) a Pearson correlation coefficient between observed_points and expected_points across the supplied rows. Both reports are derived locally from the submitted data with no external lookup.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "observed_points",
     "expected_points"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "expected_points": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "observed_points": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "expected_points": 1,
     "observed_points": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "expected_points": 2,
     "observed_points": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "expected_points": 3,
     "observed_points": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "expected_points": 4,
     "observed_points": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "observed_points",
    "expected_points"
   ],
   "type": "string",
   "default": "observed_points"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-trailing-mean-two-measure-correlation-465e3b27/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)