Average Error: 0.2 → 0.2
Time: 18.0s
Precision: 64
\[0.0 \lt m \land 0.0 \lt v \land v \lt 0.25\]
\[\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot m\]
↓
\[\left(\frac{m}{\frac{v}{1 - m}} - 1\right) \cdot m\]
\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 r20001 = m;
        double r20002 = 1.0;
        double r20003 = r20002 - r20001;
        double r20004 = r20001 * r20003;
        double r20005 = v;
        double r20006 = r20004 / r20005;
        double r20007 = r20006 - r20002;
        double r20008 = r20007 * r20001;
        return r20008;
}
↓
double f(double m, double v) {
        double r20009 = m;
        double r20010 = v;
        double r20011 = 1.0;
        double r20012 = r20011 - r20009;
        double r20013 = r20010 / r20012;
        double r20014 = r20009 / r20013;
        double r20015 = r20014 - r20011;
        double r20016 = r20015 * r20009;
        return r20016;
}

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 
(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))