Average Error: 0.2 → 0.2
Time: 4.5s
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 r12499 = m;
        double r12500 = 1.0;
        double r12501 = r12500 - r12499;
        double r12502 = r12499 * r12501;
        double r12503 = v;
        double r12504 = r12502 / r12503;
        double r12505 = r12504 - r12500;
        double r12506 = r12505 * r12499;
        return r12506;
}
↓
double f(double m, double v) {
        double r12507 = m;
        double r12508 = v;
        double r12509 = 1.0;
        double r12510 = r12509 - r12507;
        double r12511 = r12508 / r12510;
        double r12512 = r12507 / r12511;
        double r12513 = r12512 - r12509;
        double r12514 = r12513 * r12507;
        return r12514;
}

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 2020001 
(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))