als-statistics/lib/table/instruments/pearson.js

A powerful and lightweight JavaScript library for descriptive statistics, regression, clustering, outlier detection, and noise analysis using a flexible table/column architecture.

const { tCDF } = require('./cdf')
class PearsonP {
   constructor(n, cov,sigX, sigY) {
      this.r = (sigX === 0 || sigY === 0) ? 0 : cov / (sigX * sigY)
      this.df = n - 2;
      this.t = 0;
      this.p = 1;
      if (this.df > 1) this.calculateP(this)
   }

   get significant() { return this.p < 0.0001 }
   get sig() { return (this.p < 0.0001) ? "<0.0001" : this.p.toFixed(4) }
   calculateP({ r, df }) {
      this.t = r * Math.sqrt(df / Math.max(1 - r * r, 1e-16));
      this.p = 2 * (1 - tCDF(Math.abs(this.t), df));
      if (this.p < 0) this.p = 0;
      if (this.p > 1) this.p = 1;
   }
}

module.exports = PearsonP