code: function meanSquaredError(actuals, estimates) {
                const squaredErrors = forecastErrors(actuals, estimates).map(e=>e*e);
                return avg$2(squaredErrors);
              }
docs: The standard error of the estimate is a measure of the accuracy of predictions made with a regression line. Compares the estimate to the actual value
  @memberOf util
  @see {@link http://onlinestatbook.com/2/regression/accuracy.html}
  @example
  const actuals = [ 45, 38, 43, 39 ];
  const estimates = [ 41, 43, 41, 42 ];
  const MSE = ms.util.meanSquaredError(actuals, estimates); // => 13.5
  @param {Number[]} actuals - numerical samples
  @param {Number[]} estimates - estimates values
  @returns {Number} MSE