Least squares polynomial regression to 4th order in C++

Does anyone know how to modify this function to get a 4th degree polynomial regression? So that I will get the values for 'd' and 'e'. Do I need to calculate 'xm' up to x8m? Then x3ym and x4ym? I'm not sure what to do after.

void polyRegression( const std::vector<int>& x, const std::vector<int>& y 

)
{
  int n = x.size();
  std::vector<int> r(n);
  std::iota( r.begin(), r.end(), 0 );

  double xm = std::accumulate( x.begin(), x.end(), 0.0 ) / x.size();
  double ym = std::accumulate( y.begin(), y.end(), 0.0 ) / y.size();

  double x2m = std::transform_reduce( r.begin(), r.end(), 0.0, std::plus<double>{}, [](double a) {return a * a;         } ) / r.size();
  double x3m = std::transform_reduce( r.begin(), r.end(), 0.0, std::plus<double>{}, [](double a) {return a * a * a;     } ) / r.size();
  double x4m = std::transform_reduce( r.begin(), r.end(), 0.0, std::plus<double>{}, [](double a) {return a * a * a * a; } ) / r.size();

  double xym = std::transform_reduce( x.begin(), x.end(), y.begin(), 0.0, std::plus<double>{}, std::multiplies<double>{} );
  xym /= fmin( x.size(), y.size() );

  double x2ym = std::transform_reduce( x.begin(), x.end(), y.begin(), 0.0, std::plus<double>{}, [](double a, double b) { return a * a * b; } );
  x2ym /= fmin( x.size(), y.size() );

  double sxx   = x2m - xm * xm;
  double sxy   = xym - xm * ym;
  double sxx2  = x3m - xm * x2m;
  double sx2x2 = x4m - x2m * x2m;
  double sx2y  = x2ym - x2m * ym;

  double b = (sxy * sx2x2 - sx2y * sxx2) / (sxx * sx2x2 - sxx2 * sxx2);
  double c = (sx2y * sxx - sxy * sxx2) / (sxx * sx2x2 - sxx2 * sxx2);
  double a = ym - b * xm - c * x2m;

}