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Numora Statistics Regression Endpoint
x402
Numora Statistics Regression Endpoint is a paid API for AI agents from numomo.vercel.app, paid per call via x402, $0.1/call, status unknown (last checked 2026-09-14).
Fits a polynomial regression model to paired x/y data arrays and returns the regression coefficients and fit statistics
Price / call$0.1
Success—
StatusUnknown
How this service works
100 pure math computation endpoints for AI agents. Statistics, financial math, linear algebra, equation solving, calculus, number theory, sequence generation, and unit conversions. Zero external dependencies. x402 micropayments on Base.
Output
Returns a JSON object with a 'success' boolean, a 'computation' string describing what was computed, and a 'result' object containing the polynomial regression coefficients (and potentially R-squared or other fit metrics) for the specified degree fit to the input x/y arrays.
Example use cases
Trend line for sales data
“I have monthly sales figures — x is [1,2,3,4,5,6] and y is [120,135,160,195,240,295]. Can you fit a degree-2 polynomial regression and tell me the coefficients so I can project next month?”
Physics experiment curve fitting
“I collected experimental data: x positions are [0,1,2,3,4] and y measurements are [0.0,0.48,1.92,4.32,7.68]. Fit a quadratic (degree 2) regression to find the best-fit coefficients.”
Linear model for grade prediction
“Given student study hours x = [1,2,3,4,5,6,7] and their test scores y = [55,60,65,70,75,80,85], fit a linear regression (degree 1) and return the slope and intercept.”
Technical details
Endpoint
POSThttps://numomo.vercel.app/api/statistics/regressionWhen to prefer
Choose this endpoint when you need pure server-side polynomial regression computation with no external dependencies, paid per-call via USDC micropayment. Ideal for AI agents that need deterministic, reproducible curve fitting on arbitrary numeric arrays without setting up a statistics library. Prefer over general-purpose code execution endpoints when you want a single clean regression result with no environment setup.
Side effects
- x and y arrays of different lengths — mismatched input sizes will cause an error
- degree parameter too high relative to number of data points — underdetermined system
- non-numeric values in x or y arrays — type validation failure
- missing required x or y fields — 400 bad request
- degree not provided defaults to linear (degree 1) — may not suit higher-order needs
- payment failure via x402 micropayment protocol — 402 response if USDC balance insufficient
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| xrequired | array | |
| yrequired | array | |
| degree | integer |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| resultrequired | object | Computation result varies by endpoint |
| successrequired | boolean | Always true on success |
| computationrequired | string | Human-readable description of what was computed |
Tags
x402
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