Average Error: 0.1 → 0.1
Time: 1.6m
Precision: 64
Internal Precision: 320
\[\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot \left(1 - m\right)\]
\[\left(\left(\frac{m}{v} - \frac{1}{\frac{v}{{m}^{2}}}\right) - 1\right) \cdot \left(1 - m\right)\]

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 0.1

    \[\left(\frac{m \cdot \left(1 - m\right)}{v} - 1\right) \cdot \left(1 - m\right)\]
  2. Taylor expanded around -inf 0.1

    \[\leadsto \left(\color{blue}{\left(\frac{m}{v} - \frac{{m}^{2}}{v}\right)} - 1\right) \cdot \left(1 - m\right)\]
  3. Using strategy rm
  4. Applied clear-num0.1

    \[\leadsto \left(\left(\frac{m}{v} - \color{blue}{\frac{1}{\frac{v}{{m}^{2}}}}\right) - 1\right) \cdot \left(1 - m\right)\]
  5. Final simplification0.1

    \[\leadsto \left(\left(\frac{m}{v} - \frac{1}{\frac{v}{{m}^{2}}}\right) - 1\right) \cdot \left(1 - m\right)\]

Runtime

Time bar (total: 1.6m)Debug logProfile

BaselineHerbieOracleSpan%
Regimes0.10.10.00.10%
herbie shell --seed 2018263 +o rules:numerics
(FPCore (m v)
  :name "b parameter of renormalized beta distribution"
  :pre (and (< 0 m) (< 0 v) (< v 0.25))
  (* (- (/ (* m (- 1 m)) v) 1) (- 1 m)))