Average Error: 0.2 → 0.2
Time: 18.4s
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 r22911 = m;
        double r22912 = 1.0;
        double r22913 = r22912 - r22911;
        double r22914 = r22911 * r22913;
        double r22915 = v;
        double r22916 = r22914 / r22915;
        double r22917 = r22916 - r22912;
        double r22918 = r22917 * r22911;
        return r22918;
}
↓
double f(double m, double v) {
        double r22919 = m;
        double r22920 = v;
        double r22921 = 1.0;
        double r22922 = r22921 - r22919;
        double r22923 = r22920 / r22922;
        double r22924 = r22919 / r22923;
        double r22925 = r22924 - r22921;
        double r22926 = r22925 * r22919;
        return r22926;
}

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 2019235 +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))