Normal Distribution
Generates normally distributed random numbers.
Details
Normal (Gaussian) random number generator fills the input n x p numeric table with Gaussian random numbers with mean α and standard deviation σ, where α, σ∈R and σ > 0. The probability density function is given by:
The cumulative distribution function is as follows:
Batch Processing
Algorithm Parameters
Normal distribution algorithm has the following parameters in addition to the common parameters specified in Distributions:
Parameter | Default Value | Description |
|---|---|---|
algorithmFPType | float | The floating-point type that the algorithm uses for intermediate computations. Can be float or double . |
method | defaultDense | Performance-oriented computation method, the only method supported by the algorithm.
The only method supported so far is the Inverse Cumulative Distribution Function (ICDF) method. |
a | 0 | The mean  |
sigma | 1 | The standard deviation  |
Examples
Python*
Batch Processing: