Description
Normal distribution is a continuous real distribution with
density function
 ,
where  and
 > 0 are
distribution parameters. The following picture shows graphs of the
density function
f (bound to the left axis) and the
cumulative distribution function
F (bound to the right axis) with parameters
= 0,
= 1.
Characteristics
The following table contains formulae for calculation of
characteristics of normal distribution.
* Normal cumulative distribution function does not possess closed form
expression.
Simulation
A simple way of simulation normal random variables for Monte
Carlo methods consists of the following steps:
- Get 12 independent values U1, ..., U12
of a random variable with uniform distribution on [0,1].
- Calculate N = (U1 + ... + U12 - 6).
Value of N is a good approximation to a standard normal variable,
possessing parameters = 0
and = 1.
Desired result is obtained by transform
N +
.
Simulation of a uniform distribution on [0,1] is presented
here.
Sign guest book
View guest book
|
