# Sampling Observations — Trailing Mean Series + IQR Outlier Flags

> Sampling Observations — Trailing Mean Series + IQR Outlier Flags 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 flags IQR-based outliers for supplied sampling observation records with sample values and weights.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-149?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/sampling-observations-trailing-mean-series-iqr-outlier-flags-8617a759
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_m1ic9ebwF4ofJ5iQ1Y6Ff

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 sampling-observations-trailing-mean-series-iqr-outlier-flags-8617a759 -d '<json body>'
```

Example prompt: I have 150 daily sampling observations with sample_value and sample_weight fields — can you calculate the trailing mean series using a window of 7 and flag any IQR outliers for the sample_value field?

## When to prefer this

Choose this endpoint when you have tabular sampling observation data (up to 200 rows) and need both a smoothed trailing mean time series AND IQR-based outlier detection in a single low-cost call. It is ideal for quality control, sensor data review, lab measurements, or any periodic sampling workflow where trend visibility and anomaly flagging are both needed. Prefer it over generic statistics APIs when you have weighted samples with group labels and date-ordered rows.

## Known failure modes

- Input array is empty or exceeds 200 rows — request rejected
- Window size larger than number of input rows — may produce incomplete or null leading values
- Missing required fields (row_id, date, sample_value, sample_weight, dataset_group) — validation error
- Date strings not matching YYYY-MM-DD format — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — rejected
- Payment of 0.01 USDC not completed — request blocked by x402 paywall

## How this service works

Sampling observations — Trailing mean series + IQR outlier flags: Trailing mean series + IQR outlier flags for supplied sampling observations records (sample_value, sample_weight). 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 statistical reports sharing local analytical engines: (1) a trailing mean series computed over the specified rolling window for the chosen field, and (2) IQR outlier flags identifying which observation rows fall beyond 1.5 times the interquartile range. Reports cover up to 200 input rows and include per-row identifiers and dataset group context.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/sampling-observations-trailing-mean-series-iqr-outlier-flags-8617a759/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)