Average Error: 0.2 → 0.2
Time: 25.5s
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 r24506 = m;
        double r24507 = 1.0;
        double r24508 = r24507 - r24506;
        double r24509 = r24506 * r24508;
        double r24510 = v;
        double r24511 = r24509 / r24510;
        double r24512 = r24511 - r24507;
        double r24513 = r24512 * r24506;
        return r24513;
}
↓
double f(double m, double v) {
        double r24514 = m;
        double r24515 = v;
        double r24516 = 1.0;
        double r24517 = r24516 - r24514;
        double r24518 = r24515 / r24517;
        double r24519 = r24514 / r24518;
        double r24520 = r24519 - r24516;
        double r24521 = r24520 * r24514;
        return r24521;
}

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 2019325 
(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))