Average Error: 0.2 → 0.2
Time: 5.7s
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 r12867 = m;
        double r12868 = 1.0;
        double r12869 = r12868 - r12867;
        double r12870 = r12867 * r12869;
        double r12871 = v;
        double r12872 = r12870 / r12871;
        double r12873 = r12872 - r12868;
        double r12874 = r12873 * r12867;
        return r12874;
}
↓
double f(double m, double v) {
        double r12875 = m;
        double r12876 = v;
        double r12877 = 1.0;
        double r12878 = r12877 - r12875;
        double r12879 = r12876 / r12878;
        double r12880 = r12875 / r12879;
        double r12881 = r12880 - r12877;
        double r12882 = r12881 * r12875;
        return r12882;
}

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 2020036 +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))