# Description

CHAOS.MOD allows a user to determine how good or bad random numbers generated by the formula X=R*X*(1-X) are by generating a series from the formula and outputting them into a plot.

# State Variables

State Variables in CHAOS.MOD
Variable Name Variable Description Size Type
X Pseudo random number 1 Real
R Factor multiplied by X and (1-X) 1 Real

# Vertices

Vertices in CHAOS.MOD
Vertex Name Vertex Description State Changes
RUN Initialization of R and X None
DOIT Generate X X = R*X*(1-X)

# Initialization Conditions

Initialization Conditions in CHAOS.MOD
Variable Description
X Initial value of pseudo random number X
R Factor multiplied by X and (1-X)

# English Translation

An English translation is a verbal description of a model, automatically generated by SIGMA.

```The SIGMA Model, CHAOS.MOD, is a discrete event simulation.
It models CHAOS (X=R*X*(1-X)) GOOD OR BAD RANDOM NUMBERS?.
```
```I. STATE VARIABLE DEFINITIONS.
```
```For this simulation, the following state variables are defined:
```
```X:   (real valued)
R:   (real valued)
```
```II. EVENT DEFINITIONS.
```
```Simulation state changes are represented by event vertices (nodes or balls) in a SIGMA graph.
Event vertex parameters, if any, are given in parentheses. Logical and dynamic relationships
between pairs of events are represented in a SIGMA graph by edges (arrows) between event vertices.
Unless otherwise stated, vertex execution priorities, to break time ties, are equal to 5.
```
```1. The RUN(R,X) event:
Initial values for, R,X, are needed for each run.
After every occurrence of the RUN event:
Unconditionally, schedule the DOIT() event to occur without delay.
```
```2. The DOIT() event:
This event causes the following state change(s):
X = R*X*(1-X)
After every occurrence of the DOIT event:
Unconditionally, schedule the DOIT() event to occur in 1 time units.
```