Average Error: 0.2 → 0.2
Time: 15.0s
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 r13270 = m;
        double r13271 = 1.0;
        double r13272 = r13271 - r13270;
        double r13273 = r13270 * r13272;
        double r13274 = v;
        double r13275 = r13273 / r13274;
        double r13276 = r13275 - r13271;
        double r13277 = r13276 * r13270;
        return r13277;
}
↓
double f(double m, double v) {
        double r13278 = 1.0;
        double r13279 = v;
        double r13280 = m;
        double r13281 = 1.0;
        double r13282 = r13281 - r13280;
        double r13283 = r13280 * r13282;
        double r13284 = r13279 / r13283;
        double r13285 = r13278 / r13284;
        double r13286 = r13285 - r13281;
        double r13287 = r13286 * r13280;
        return r13287;
}

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 2019351 +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))