Average Error: 0.2 → 0.2
Time: 6.3s
Precision: 64
\[0.0 \lt m \land 0.0 \lt v \land v \lt 0.25\]
\[\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot m\]
↓
\[\left(\frac{m}{\frac{v}{1 - m}} - 1\right) \cdot m\]
\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot m
↓
\left(\frac{m}{\frac{v}{1 - m}} - 1\right) \cdot m
double f(double m, double v) {
        double r17750 = m;
        double r17751 = 1.0;
        double r17752 = r17751 - r17750;
        double r17753 = r17750 * r17752;
        double r17754 = v;
        double r17755 = r17753 / r17754;
        double r17756 = r17755 - r17751;
        double r17757 = r17756 * r17750;
        return r17757;
}
↓
double f(double m, double v) {
        double r17758 = m;
        double r17759 = v;
        double r17760 = 1.0;
        double r17761 = r17760 - r17758;
        double r17762 = r17759 / r17761;
        double r17763 = r17758 / r17762;
        double r17764 = r17763 - r17760;
        double r17765 = r17764 * r17758;
        return r17765;
}

Error

Bits error versus m

Bits error versus v

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.2

    \[\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot m\]
  2. Using strategy rm

  3. Applied associate-/l*0.2

    \[\leadsto \left(\color{blue}{\frac{m}{\frac{v}{1 - m}}} - 1\right) \cdot m\]

  4. Final simplification0.2

    \[\leadsto \left(\frac{m}{\frac{v}{1 - m}} - 1\right) \cdot m\]

Reproduce

herbie shell --seed 2020024 +o rules:numerics
(FPCore (m v)
  :name "a parameter of renormalized beta distribution"
  :precision binary64
  :pre (and (< 0.0 m) (< 0.0 v) (< v 0.25))
  (* (- (/ (* m (- 1 m)) v) 1) m))