Average Error: 0.2 → 0.2
Time: 5.8s
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 r14715 = m;
        double r14716 = 1.0;
        double r14717 = r14716 - r14715;
        double r14718 = r14715 * r14717;
        double r14719 = v;
        double r14720 = r14718 / r14719;
        double r14721 = r14720 - r14716;
        double r14722 = r14721 * r14715;
        return r14722;
}
↓
double f(double m, double v) {
        double r14723 = m;
        double r14724 = v;
        double r14725 = 1.0;
        double r14726 = r14725 - r14723;
        double r14727 = r14724 / r14726;
        double r14728 = r14723 / r14727;
        double r14729 = r14728 - r14725;
        double r14730 = r14729 * r14723;
        return r14730;
}

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 +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))