npm install @tpmjs/tools-linear-regression-ols

import { linearRegressionOLSTool } from '@tpmjs/tools-linear-regression-ols';

// Use with AI SDK
const result = await linearRegressionOLSTool.execute({
  x: [1, 2, 3, 4, 5],
  y: [2, 4, 5, 4, 5],
});

console.log(result);
// {
//   slope: 0.6,
//   intercept: 2.2,
//   rSquared: 0.581,
//   residuals: [-0.8, 0.6, 0.4, -0.6, 0.4],
//   predictions: [2.8, 3.4, 4.0, 4.6, 5.2],
//   metadata: {
//     n: 5,
//     meanX: 3,
//     meanY: 4,
//     sst: 5,
//     sse: 2.096
//   }
// }

{
  slope: number;              // Slope of the regression line (β₁)
  intercept: number;          // Y-intercept (β₀)
  rSquared: number;           // Coefficient of determination (0-1)
  residuals: number[];        // Residuals (y - ŷ) for each point
  predictions: number[];      // Predicted values (ŷ) for each x
  metadata: {
    n: number;                // Number of observations
    meanX: number;            // Mean of x values
    meanY: number;            // Mean of y values
    sst: number;              // Total sum of squares
    sse: number;              // Sum of squared errors
  }
}

const result = await linearRegressionOLSTool.execute({
  x: [1, 2, 3, 4, 5],
  y: [2.1, 3.9, 6.2, 7.8, 10.1],
});

// Use slope and intercept to predict new values
const predictY = (x: number) => result.intercept + result.slope * x;

console.log(predictY(6));  // Predict y for x=6
// Output: ~12.0