Average Error: 2.0 → 0.5
Time: 8.9s
Precision: binary64
\[\]
↓
\[\]
↓
double code(double x, double y, double z, double t, double a, double b) {
	return ((double) (x * ((double) exp(((double) (((double) (y * ((double) (((double) log(z)) - t)))) + ((double) (a * ((double) (((double) log(((double) (1.0 - z)))) - b))))))))));
}

↓
double code(double x, double y, double z, double t, double a, double b) {
	return ((double) (((double) (x * ((double) pow(((double) M_E), ((double) (0.5 * ((double) cbrt(((double) pow(((double) (((double) (y * ((double) (((double) log(z)) - t)))) + ((double) (a * ((double) (((double) log(1.0)) - ((double) (((double) (z * 1.0)) + ((double) (((double) (0.5 * ((double) (((double) (z / 1.0)) * ((double) (z / 1.0)))))) + b)))))))))), 3.0)))))))))) * ((double) pow(((double) M_E), ((double) (((double) (((double) (y * ((double) (((double) log(z)) - t)))) + ((double) (a * ((double) (((double) (((double) log(1.0)) - ((double) (((double) (z * 1.0)) + ((double) (0.5 * ((double) (((double) (z / 1.0)) * ((double) (z / 1.0)))))))))) - b)))))) / 2.0))))));
}

Error
Bits error versus x
Bits error versus y
Bits error versus z
Bits error versus t
Bits error versus a
Bits error versus b
Try it out
Your Program's Arguments
Results
Enter valid numbers for all inputs
Derivation
  1. Initial program 2.0
    \[\]
  2. Taylor expanded around 0 0.5
    \[\leadsto \]
  3. Simplified0.5
    \[\leadsto \]
  4. Using strategy rm
  5. Applied *-un-lft-identity0.5
    \[\leadsto \]
  6. Applied exp-prod0.5
    \[\leadsto \]
  7. Simplified0.5
    \[\leadsto \]
  8. Using strategy rm
  9. Applied sqr-pow0.5
    \[\leadsto \]
  10. Applied associate-*r*0.5
    \[\leadsto \]
  11. Simplified0.5
    \[\leadsto \]
  12. Using strategy rm
  13. Applied add-cbrt-cube0.5
    \[\leadsto \]
  14. Simplified0.5
    \[\leadsto \]
  15. Final simplification0.5
    \[\leadsto \]
Reproduce
herbie shell --seed 2020179 
(FPCore (x y z t a b)
  :name "Numeric.SpecFunctions:incompleteBetaApprox from math-functions-0.1.5.2, B"
  :precision binary64
  (* x (exp (+ (* y (- (log z) t)) (* a (- (log (- 1.0 z)) b))))))