prnorm

Generating numbers form Normal distribution
here we use Box Muler transform to obtain normal random variable

Provides functions for generating pseudo-random numbers that follow a uniform distribution [0,1]. Randomness tests were conducted using the National Institute of Standards and Technology test suite<https://csrc.nist.gov/pubs/sp/800/22/r1/upd1/final>, along with additional tests. The sequence generated depends on the initial values and parameters. The package includes a linear congruence map as the decision map and three chaotic maps to generate the pseudo-random sequence, which follow a uniform distribution. Other distributions can be generated from the uniform distribution using the Inversion Principle Method and BOX-Muller transformation. Small perturbations in seed values result in entirely different sequences of numbers due to the sensitive nature of the maps being used. The chaotic nature of the maps helps achieve randomness in the generator. Additionally, the generator is capable of producing random bits.

Sajad Ahmad Mir

PRNG

A Pseudo-Random Number Generator

Dr. Puneet Sharma

prnorm function

<dl><dt>n</dt>
<dd>number required</dd></dl>

Arguments

Generating numbers form    Normal distribution
here we use  Box Muler transform to obtain normal random variable — prnorm

<dl>

<dt>n</dt>
<dd>number required</dd>

</dl>

prnorm: Generating numbers form Normal distribution here we use Box Muler transform to obtain normal random variable

Description

Usage

Value

Arguments

Examples