b parameter of renormalized beta distribution

Average Error: 0.1 → 0.1

Time: 6.6s

Precision: binary64

\[0 < m \land 0 < v \land v < 0.25\]

Math

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

↓

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

FPCore

(FPCore (m v) :precision binary64 (* (- (/ (* m (- 1.0 m)) v) 1.0) (- 1.0 m)))

↓

(FPCore (m v)
 :precision binary64
 (+ (+ (+ m (/ m v)) (* (* m (/ m v)) (- m 2.0))) -1.0))

C

double code(double m, double v) {
	return (((m * (1.0 - m)) / v) - 1.0) * (1.0 - m);
}

↓

double code(double m, double v) {
	return ((m + (m / v)) + ((m * (m / v)) * (m - 2.0))) + -1.0;
}

Error

Bits error versus m

Bits error versus v

Derivation

1. Initial program 0.1

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

2. Applied add-sqr-sqrt_binary64 0.3

   \[\leadsto \left(\frac{m \cdot \left(1 - m\right)}{\color{blue}{\sqrt{v} \cdot \sqrt{v}}} - 1\right) \cdot \left(1 - m\right) \]

3. Applied times-frac_binary64 0.4

   \[\leadsto \left(\color{blue}{\frac{m}{\sqrt{v}} \cdot \frac{1 - m}{\sqrt{v}}} - 1\right) \cdot \left(1 - m\right) \]

4. Taylor expanded in m around 0 0.1

   \[\leadsto \color{blue}{\left(\frac{{m}^{3}}{v} + \left(\frac{m}{v} + m\right)\right) - \left(1 + 2 \cdot \frac{{m}^{2}}{v}\right)} \]

5. Simplified 0.1

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

6. Final simplification 0.1

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

Reproduce

herbie shell --seed 2021215 
(FPCore (m v)
  :name "b parameter of renormalized beta distribution"
  :precision binary64
  :pre (and (< 0.0 m) (< 0.0 v) (< v 0.25))
  (* (- (/ (* m (- 1.0 m)) v) 1.0) (- 1.0 m)))