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Distribution ​

Values for variables in ADOxx are assigned using Random Generator objects. The kind of value assignment can vary; for instance this could be done via distributions. The following distribution types are possible:

  • Continuous distribution functions: exponential, uniform, and normal distribution; for variables of the type Double.

  • Discrete distribution: for variables of the type Enumeration.

Syntax of the continuous distribution functions:

  • for normal distribution: normal (<number1>;<number2>) Enter the expected value and the standard deviation for the normal distribution, where <number1> represents the expected value and <number2> stands for the standard deviation. Example: Normal(1200;100)The variable has a normal distribution with an expected value of 1200 and a standard deviation of 100.

  • For exponential distribution: exponential (<number>) Enter the expected value of the exponential distribution, letting <number> be 1 divided by the expected value. Example: Exponential(0,002)The variable has an exponential distribution with an expected value of 500.

  • For uniform distribution: uniform (<number1>;<number2>) Enter the boundaries for the uniform distribution, where <number1> indicates the lower boundary and <number2> the upper boundary. Example: Uniform(0;100)The variable is uniformly distributed between the boundaries 0 and 100.

Syntax of the discrete distribution:

Discrete (<Symbol1> <number1>;<Symbol2> <number2>; ...)

You can define two or more symbols with their corresponding probabilities (number1, number2,...). The sum of the probabilities must always equal one!

Attention

The entry of symbol names is case-sensitive. The symbol names shall not start with numerals from 0 to 9, blanks or returns and the figures : ( ) . , ; '. Also blanks and returns, as well as the figures: ( ) . , ; ' arenot authorised in symbol names.

Examples:

Discrete (YES 0.6;NO 0.4):

The variable is assigned with a probability of 0.6 of being 'YES' and a probability of 0.4 of being 'NO'. Therefore two transition conditions <variable name>='YES' and <variable name>='NO' are valid and possible.

Discrete (a 0.5;b 0.3;c 0.1;d 0.1):

The variable is assigned with a probability of 0.5 of taking the value 'a', a probability of 0.3 of being 'b', a probability of 0.1 of taking the value 'c' and a probability of 0.1 of taking the value 'd'. The four possible transition conditions therefore are: <variable name>='a', <variable name>='b', <variable name>='c' and <variable name>='d'.