Average Error: 0.2 → 0.2
Time: 4.2s
Precision: 64
\[0.0 \lt m \land 0.0 \lt v \land v \lt 0.25\]
\[\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot m\]
↓
\[\left(\frac{1}{\frac{v}{m \cdot \left(1 - m\right)}} - 1\right) \cdot m\]
\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot m
↓
\left(\frac{1}{\frac{v}{m \cdot \left(1 - m\right)}} - 1\right) \cdot m
double f(double m, double v) {
        double r11194 = m;
        double r11195 = 1.0;
        double r11196 = r11195 - r11194;
        double r11197 = r11194 * r11196;
        double r11198 = v;
        double r11199 = r11197 / r11198;
        double r11200 = r11199 - r11195;
        double r11201 = r11200 * r11194;
        return r11201;
}
↓
double f(double m, double v) {
        double r11202 = 1.0;
        double r11203 = v;
        double r11204 = m;
        double r11205 = 1.0;
        double r11206 = r11205 - r11204;
        double r11207 = r11204 * r11206;
        double r11208 = r11203 / r11207;
        double r11209 = r11202 / r11208;
        double r11210 = r11209 - r11205;
        double r11211 = r11210 * r11204;
        return r11211;
}

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 clear-num0.2

    \[\leadsto \left(\color{blue}{\frac{1}{\frac{v}{m \cdot \left(1 - m\right)}}} - 1\right) \cdot m\]

  4. Final simplification0.2

    \[\leadsto \left(\frac{1}{\frac{v}{m \cdot \left(1 - m\right)}} - 1\right) \cdot m\]

Reproduce

herbie shell --seed 2020002 
(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))