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agent402.tools Forecast Evaluation (Backtest)
x402
agent402.tools Forecast Evaluation (Backtest) is a paid API for AI agents from agent402.tools, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-14).
Backtests a time-series forecasting method by holding out the last N observations, generating forecasts, and returning MAPE and RMSE accuracy metrics.
Price / call$0.001
Success—
StatusUnknown
How this service works
Backtest a forecasting method on the input series by holding out the last `testSize` observations, forecasting them, and computing MAPE (mean absolute percentage error) + RMSE (root mean squared error). Lets an agent pick which method (mean / naive / drift / ses / holt / holt-winters) actually fits its data before committing to a forward forecast.
Output
Returns MAPE (mean absolute percentage error) and RMSE (root mean squared error) computed over the held-out test observations, along with possibly a warning if testSize exceeds half the series length.
Example use cases
Example prompt
“Backtest the Holt-Winters method on my sales data — here are the 120 monthly values: [23, 45, 67, ...] — hold out the last 12 observations as the test set, use an additive seasonality with period 12, and tell me the MAPE and RMSE.”
Technical details
Endpoint
POSThttps://agent402.tools/api/forecast-evalWhen to prefer
Use this endpoint when you need to objectively measure how well a specific statistical forecasting method (mean, naive, drift, SES, Holt, Holt-Winters) fits a given numeric time series, using held-out test data, without building a full ML pipeline. Ideal for lightweight model selection or benchmarking before committing to a forecasting strategy.
Side effects
- testSize less than 1 or greater than values.length - 2 returns a validation error
- series too short for the chosen method or seasonal period
- invalid method string returns an error
- holt-winters without sufficient seasonal cycles may fail or warn
- values array exceeding 10000 elements rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| beta | number | Trend smoothing for holt/holt-winters |
| alpha | number | Smoothing for ses/holt/holt-winters |
| gamma | number | Seasonal smoothing for holt-winters |
| method | string | "mean", "naive", "drift", "ses", "holt", "holt-winters" |
| period | number | Seasonal period for holt-winters (auto-detected if omitted) |
| values | array | Numeric series (max 10000) |
| testSize | number | Trailing observations to hold out (1 to values.length - 2). Values above n/2 trigger a warning, not an error. |
| seasonality | string | "additive" or "multiplicative" for holt-winters |
Output
Schema · Response
{
"type": "json",
"example": {
"n": 10,
"mape": 1.1139,
"rmse": 0.2722,
"method": "drift",
"forecast": [
{
"step": 1,
"actual": 19,
"predicted": 19.3333
},
{
"step": 2,
"actual": 21,
"predicted": 20.6667
},
{
"step": 3,
"actual": 22,
"predicted": 22
}
],
"testSize": 3,
"warnings": [],
"trainSize": 7
}
}Tags
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