CHAOS.MOD

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Contents

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)

Event Relationship Graph

CHAOS.MOD
CHAOS.MOD

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.

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