Average Error: 0.2 → 0.2
Time: 4.5s
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 r13239 = m;
        double r13240 = 1.0;
        double r13241 = r13240 - r13239;
        double r13242 = r13239 * r13241;
        double r13243 = v;
        double r13244 = r13242 / r13243;
        double r13245 = r13244 - r13240;
        double r13246 = r13245 * r13239;
        return r13246;
}
↓
double f(double m, double v) {
        double r13247 = 1.0;
        double r13248 = v;
        double r13249 = m;
        double r13250 = 1.0;
        double r13251 = r13250 - r13249;
        double r13252 = r13249 * r13251;
        double r13253 = r13248 / r13252;
        double r13254 = r13247 / r13253;
        double r13255 = r13254 - r13250;
        double r13256 = r13255 * r13249;
        return r13256;
}

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 2020049 +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))