# Forecast Verification IQR Outlier Flags + Secondary-Measure Weighted Mean

> 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.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-24-177?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/forecast-verification-iqr-outlier-flags-secondary-measure-weighted-mean-baf5db9e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_eDywHZsxTJ9Jb709X6aBL

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 forecast-verification-iqr-outlier-flags-secondary-measure-weighted-mean-baf5db9e -d '<json body>'
```

Example prompt: Can you run IQR outlier flagging and a secondary-measure weighted mean on my forecast verification data? I have rows with forecast_value and observed_value for station groups across dates in October 2026 — up to 4 rows, and I want to analyze the forecast_value field.

## When to prefer this

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.

## Known failure modes

- 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

## 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.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/forecast-verification-iqr-outlier-flags-secondary-measure-weighted-mean-baf5db9e/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)