code: function adjustedCoefficentOfDetermination(options = {}) {
                const { actuals, estimates, rSquared, independentVariables, sampleSize, } = options;
                const r2 = rSquared || coefficientOfDetermination(actuals, estimates);
                const n = sampleSize || actuals.length;
                const k = independentVariables;
  
                return (1 - (1 - r2) * ((n - 1) / (n - (k + 1))));
              }
docs: You can use the adjusted coefficient of determination to determine how well a multiple regression equation “fits” the sample data. The adjusted coefficient of determination is closely related to the coefficient of determination (also known as R2) that you use to test the results of a simple regression equation.
  @example
  const adjr2 = ms.util.adjustedCoefficentOfDetermination({
  rSquared: 0.944346527,
  sampleSize: 8,
  independentVariables: 2,
  });
  r2.toFixed(3) // => 0.922
  @memberOf util
  @see {@link http://www.dummies.com/education/math/business-statistics/how-to-calculate-the-adjusted-coefficient-of-determination/}
  @param {Object} [options={}]
  @param {Number[]} [options.actuals] - numerical samples
  @param {Number[]} [options.estimates] - estimate values
  @param {Number} [options.rSquared] - coefficent of determination
  @param {Number} [options.sampleSize] - the sample size
  @param {Number} options.independentVariables - the number of independent variables in the regression equation
  @returns {Number} adjusted r^2 for multiple linear regression