Average Error: 0.2 → 0.2
Time: 4.2s
Precision: 64
\[0.0 \lt m \land 0.0 \lt v \land v \lt 0.25\]
\[\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot m\]
↓
\[\left(\frac{1}{\frac{v}{m \cdot \left(1 - m\right)}} - 1\right) \cdot m\]
\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot m
↓
\left(\frac{1}{\frac{v}{m \cdot \left(1 - m\right)}} - 1\right) \cdot m
double f(double m, double v) {
        double r12711 = m;
        double r12712 = 1.0;
        double r12713 = r12712 - r12711;
        double r12714 = r12711 * r12713;
        double r12715 = v;
        double r12716 = r12714 / r12715;
        double r12717 = r12716 - r12712;
        double r12718 = r12717 * r12711;
        return r12718;
}
↓
double f(double m, double v) {
        double r12719 = 1.0;
        double r12720 = v;
        double r12721 = m;
        double r12722 = 1.0;
        double r12723 = r12722 - r12721;
        double r12724 = r12721 * r12723;
        double r12725 = r12720 / r12724;
        double r12726 = r12719 / r12725;
        double r12727 = r12726 - r12722;
        double r12728 = r12727 * r12721;
        return r12728;
}

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 clear-num0.2

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

  4. Final simplification0.2

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

Reproduce

herbie shell --seed 2020049 
(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))