Average Error: 0.1 → 0.1
Time: 4.2s
Precision: 64
\[\left(x \cdot \log y - z\right) - y\]
↓
\[x \cdot \log y - \left(z + y\right)\]
\left(x \cdot \log y - z\right) - y
↓
x \cdot \log y - \left(z + y\right)
double f(double x, double y, double z) {
        double r17080 = x;
        double r17081 = y;
        double r17082 = log(r17081);
        double r17083 = r17080 * r17082;
        double r17084 = z;
        double r17085 = r17083 - r17084;
        double r17086 = r17085 - r17081;
        return r17086;
}
↓
double f(double x, double y, double z) {
        double r17087 = x;
        double r17088 = y;
        double r17089 = log(r17088);
        double r17090 = r17087 * r17089;
        double r17091 = z;
        double r17092 = r17091 + r17088;
        double r17093 = r17090 - r17092;
        return r17093;
}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.1

    \[\left(x \cdot \log y - z\right) - y\]
  2. Using strategy rm

  3. Applied associate--l-0.1

    \[\leadsto \color{blue}{x \cdot \log y - \left(z + y\right)}\]

  4. Final simplification0.1

    \[\leadsto x \cdot \log y - \left(z + y\right)\]

Reproduce

herbie shell --seed 2019354 +o rules:numerics
(FPCore (x y z)
  :name "Statistics.Distribution.Poisson:$clogProbability from math-functions-0.1.5.2"
  :precision binary64
  (- (- (* x (log y)) z) y))