Average Error: 0.2 → 0.2
Time: 27.7s
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 r30653 = m;
        double r30654 = 1.0;
        double r30655 = r30654 - r30653;
        double r30656 = r30653 * r30655;
        double r30657 = v;
        double r30658 = r30656 / r30657;
        double r30659 = r30658 - r30654;
        double r30660 = r30659 * r30653;
        return r30660;
}
↓
double f(double m, double v) {
        double r30661 = m;
        double r30662 = v;
        double r30663 = 1.0;
        double r30664 = r30663 - r30661;
        double r30665 = r30662 / r30664;
        double r30666 = r30661 / r30665;
        double r30667 = r30666 - r30663;
        double r30668 = r30667 * r30661;
        return r30668;
}

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 2019326 +o rules:numerics
(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))