Average Error: 0.1 → 0.1
Time: 3.4s
Precision: binary64
\[\left(x \cdot \log y - z\right) - y\]
↓
\[\left(\left(x \cdot \log \left(\sqrt{y}\right) + x \cdot \log \left(\sqrt{y}\right)\right) - z\right) - y\]
\left(x \cdot \log y - z\right) - y
↓
\left(\left(x \cdot \log \left(\sqrt{y}\right) + x \cdot \log \left(\sqrt{y}\right)\right) - z\right) - y
(FPCore (x y z) :precision binary64 (- (- (* x (log y)) z) y))
↓
(FPCore (x y z)
 :precision binary64
 (- (- (+ (* x (log (sqrt y))) (* x (log (sqrt y)))) 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 (((x * log(sqrt(y))) + (x * log(sqrt(y)))) - z) - y;
}

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 add-sqr-sqrt_binary64_1000.1

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

  4. Applied log-prod_binary64_1640.1

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

  5. Applied distribute-rgt-in_binary64_280.1

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

  6. Simplified0.1

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

  7. Simplified0.1

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

  8. Final simplification0.1

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

Reproduce

herbie shell --seed 2020356 
(FPCore (x y z)
  :name "Statistics.Distribution.Poisson:$clogProbability from math-functions-0.1.5.2"
  :precision binary64
  (- (- (* x (log y)) z) y))