IIDNORM.MOD

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See also: How to read .MOD pages

1 Description
2 State Variables
3 Vertices
4 Initialization Conditions
5 Event Relationship Graph
6 English Translation
7 Comments

Description

IIDNORM.MOD demonstrates the following functions that are related to IID (independent and identically distributed) normal random variables:

1.NOR{M,S}: Generates a normal (M,S2) pseudo random variate

2.STS{X}: Area under the standardized time series for the traced variable X

3.VAR{X}: Cumulative variance of a traced variable X

State Variables

**State Variables in IIDNORM.MOD**
Variable Name	Variable Description	Size	Type
X	IID Pseudo-Normal variates	1	Real
S	Sample Standard Deviation	1	Real
STS	Area under STS function	1	Real
MEAN	Mean value of iid pseudo-normal variates	1	Real
STD	Standard deviation of iid pseudo-normals	1	Real

Vertices

**Vertices in IIDNORM.MOD**
Vertex Name	Vertex Description	State Changes
RUN	The simulation is started	Transaction termination counter for run
GEN	Generate X	X=NOR{MEAN;STD},S=VAR{X}^.5,STS=STS{X}

Initialization Conditions

**Initialization Conditions in IIDNORM.MOD**
Variable	Description
MEAN	Mean value of iid pseudo-normal variates
STD	Standard deviation of iid pseudo-normals

Event Relationship Graph

IIDNORM.MOD

English Translation

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

The SIGMA Model, IIDNORM.MOD, is a discrete event simulation. 
It models Statistical functions of iid Normal Variates.

I. STATE VARIABLE DEFINITIONS.

For this simulation, the following state variables are defined:

X: IID Pseudo-Normal variates  (real valued)
MEAN: Mean value of iid pseudo-normal variates  (real valued)
STD: Standard deviation of iid pseudo-normals  (real valued)
S: Sample Standard Deviation  (real valued)
STS: Area under STS function  (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(MEAN,STD) event:
   Initial values for, MEAN,STD, are needed for each run.
   After every occurrence of the RUN event:
   Unconditionally, schedule the GEN() event to occur in 1 time units.

2. The GEN() event:
   This event causes the following state change(s):
   X=NOR{MEAN;STD}
   S=VAR{X}^.5
   STS=STS{X}
   After every occurrence of the GEN event:
   Unconditionally, schedule the GEN() event to occur in 1 time units.