Average Error: 0.1 → 0.1
Time: 10.2s
Precision: binary64
\[\left(x \cdot \log y - z\right) - y \]
\[\left(\mathsf{fma}\left(x, \log \left(\sqrt[3]{y}\right) \cdot 2, x \cdot \log \left({y}^{0.16666666666666666} \cdot {y}^{0.16666666666666666}\right)\right) - z\right) - y \]
\left(x \cdot \log y - z\right) - y
\left(\mathsf{fma}\left(x, \log \left(\sqrt[3]{y}\right) \cdot 2, x \cdot \log \left({y}^{0.16666666666666666} \cdot {y}^{0.16666666666666666}\right)\right) - z\right) - y
(FPCore (x y z) :precision binary64 (- (- (* x (log y)) z) y))
(FPCore (x y z)
 :precision binary64
 (-
  (-
   (fma
    x
    (* (log (cbrt y)) 2.0)
    (* x (log (* (pow y 0.16666666666666666) (pow y 0.16666666666666666)))))
   z)
  y))
double code(double x, double y, double z) {
	return ((x * log(y)) - z) - y;
}
double code(double x, double y, double z) {
	return (fma(x, (log(cbrt(y)) * 2.0), (x * log(pow(y, 0.16666666666666666) * pow(y, 0.16666666666666666)))) - z) - y;
}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Derivation

  1. Initial program 0.1

    \[\left(x \cdot \log y - z\right) - y \]
  2. Applied add-cube-cbrt_binary640.1

    \[\leadsto \left(x \cdot \log \color{blue}{\left(\left(\sqrt[3]{y} \cdot \sqrt[3]{y}\right) \cdot \sqrt[3]{y}\right)} - z\right) - y \]
  3. Applied log-prod_binary640.1

    \[\leadsto \left(x \cdot \color{blue}{\left(\log \left(\sqrt[3]{y} \cdot \sqrt[3]{y}\right) + \log \left(\sqrt[3]{y}\right)\right)} - z\right) - y \]
  4. Applied distribute-rgt-in_binary640.1

    \[\leadsto \left(\color{blue}{\left(\log \left(\sqrt[3]{y} \cdot \sqrt[3]{y}\right) \cdot x + \log \left(\sqrt[3]{y}\right) \cdot x\right)} - z\right) - y \]
  5. Simplified0.1

    \[\leadsto \left(\left(\color{blue}{x \cdot \left(\log \left(\sqrt[3]{y}\right) \cdot 2\right)} + \log \left(\sqrt[3]{y}\right) \cdot x\right) - z\right) - y \]
  6. Simplified0.1

    \[\leadsto \left(\left(x \cdot \left(\log \left(\sqrt[3]{y}\right) \cdot 2\right) + \color{blue}{x \cdot \log \left(\sqrt[3]{y}\right)}\right) - z\right) - y \]
  7. Applied fma-def_binary640.1

    \[\leadsto \left(\color{blue}{\mathsf{fma}\left(x, \log \left(\sqrt[3]{y}\right) \cdot 2, x \cdot \log \left(\sqrt[3]{y}\right)\right)} - z\right) - y \]
  8. Applied add-sqr-sqrt_binary640.1

    \[\leadsto \left(\mathsf{fma}\left(x, \log \left(\sqrt[3]{y}\right) \cdot 2, x \cdot \log \color{blue}{\left(\sqrt{\sqrt[3]{y}} \cdot \sqrt{\sqrt[3]{y}}\right)}\right) - z\right) - y \]
  9. Simplified0.1

    \[\leadsto \left(\mathsf{fma}\left(x, \log \left(\sqrt[3]{y}\right) \cdot 2, x \cdot \log \left(\color{blue}{{y}^{0.16666666666666666}} \cdot \sqrt{\sqrt[3]{y}}\right)\right) - z\right) - y \]
  10. Simplified0.1

    \[\leadsto \left(\mathsf{fma}\left(x, \log \left(\sqrt[3]{y}\right) \cdot 2, x \cdot \log \left({y}^{0.16666666666666666} \cdot \color{blue}{{y}^{0.16666666666666666}}\right)\right) - z\right) - y \]
  11. Final simplification0.1

    \[\leadsto \left(\mathsf{fma}\left(x, \log \left(\sqrt[3]{y}\right) \cdot 2, x \cdot \log \left({y}^{0.16666666666666666} \cdot {y}^{0.16666666666666666}\right)\right) - z\right) - y \]

Reproduce

herbie shell --seed 2022097 
(FPCore (x y z)
  :name "Statistics.Distribution.Poisson:$clogProbability from math-functions-0.1.5.2"
  :precision binary64
  (- (- (* x (log y)) z) y))