Average Error: 0.2 → 0.2
Time: 23.9s
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 r18910 = m;
        double r18911 = 1.0;
        double r18912 = r18911 - r18910;
        double r18913 = r18910 * r18912;
        double r18914 = v;
        double r18915 = r18913 / r18914;
        double r18916 = r18915 - r18911;
        double r18917 = r18916 * r18910;
        return r18917;
}
↓
double f(double m, double v) {
        double r18918 = m;
        double r18919 = v;
        double r18920 = 1.0;
        double r18921 = r18920 - r18918;
        double r18922 = r18919 / r18921;
        double r18923 = r18918 / r18922;
        double r18924 = r18923 - r18920;
        double r18925 = r18924 * r18918;
        return r18925;
}

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 +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))