CumulativeNormalHastings 
Hastings algorithm is faster but less accurate way to compute the cumulative standard Normal.

CumulativeNormalInverse 
The inverse of the cumulative standard Normal distribution function is defined as:
\[
N^{1}(u)
/]

CumulativeNormalMarsaglia 
Marsaglia is about 3 times slower but is more accurate to compute the cumulative standard Normal.

Erf 
The Error function is defined as:
\[
\operatorname{erf}(x) = \frac{2}{\sqrt{\pi}}\int_{0}^x e^{t^2} dt
\]

Erfc 
This complementary Error function is defined as:
\[
\operatorname{erfc}(x)
= 1\operatorname{erf}(x)
= \frac{2}{\sqrt{\pi}} \int_x^{\infty} e^{t^2}\,dt
\]

ErfInverse 
The inverse of the Error function is defined as:
\[
\operatorname{erf}^{1}(x)
\]

Gaussian 
The Gaussian function is defined as:
\[
f(x) = a e^{ { \frac{(xb)^2 }{ 2 c^2} } }
\]
