Average Error: 0.2 → 0.2
Time: 26.8s
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 r21781 = m;
        double r21782 = 1.0;
        double r21783 = r21782 - r21781;
        double r21784 = r21781 * r21783;
        double r21785 = v;
        double r21786 = r21784 / r21785;
        double r21787 = r21786 - r21782;
        double r21788 = r21787 * r21781;
        return r21788;
}
↓
double f(double m, double v) {
        double r21789 = m;
        double r21790 = v;
        double r21791 = 1.0;
        double r21792 = r21791 - r21789;
        double r21793 = r21790 / r21792;
        double r21794 = r21789 / r21793;
        double r21795 = r21794 - r21791;
        double r21796 = r21795 * r21789;
        return r21796;
}

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 2019199 +o rules:numerics
(FPCore (m v)
  :name "a parameter of renormalized beta distribution"
  :pre (and (< 0.0 m) (< 0.0 v) (< v 0.25))
  (* (- (/ (* m (- 1.0 m)) v) 1.0) m))