Average Error: 0.2 → 0.2
Time: 10.0s
Precision: 64
\[0.0 \lt m \land 0.0 \lt v \land v \lt 0.25\]
\[\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot m\]
↓
\[\left(\frac{\frac{m}{v}}{\frac{1}{1 - m}} - 1\right) \cdot m\]
\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot m
↓
\left(\frac{\frac{m}{v}}{\frac{1}{1 - m}} - 1\right) \cdot m
double f(double m, double v) {
        double r64 = m;
        double r65 = 1.0;
        double r66 = r65 - r64;
        double r67 = r64 * r66;
        double r68 = v;
        double r69 = r67 / r68;
        double r70 = r69 - r65;
        double r71 = r70 * r64;
        return r71;
}
↓
double f(double m, double v) {
        double r72 = m;
        double r73 = v;
        double r74 = r72 / r73;
        double r75 = 1.0;
        double r76 = 1.0;
        double r77 = r76 - r72;
        double r78 = r75 / r77;
        double r79 = r74 / r78;
        double r80 = r79 - r76;
        double r81 = r80 * r72;
        return r81;
}

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. Using strategy rm

  5. Applied div-inv0.2

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

  6. Applied associate-/r*0.2

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

  7. Final simplification0.2

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

Reproduce

herbie shell --seed 2020025 
(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))