Tutorial: Arrays

Analytica Tutorial >

This chapter shows you how to:

• Create and define an Index
• Define an array variable as a Table
• Understand principles of array abstraction when combining arrays in an expression
• Use conditional expressions and logical values when defining an array
• Define variables using Expression syntax
• Use local variables to simplify an expression
• Analyze a multi-dimensional result by pivoting indexes
• Reduce an array using subscripts
• Use array reducing functions such as Sum() and NPV()

This chapter demonstrates Intelligent Arrays, one of the most powerful features of Analytica. An array can be generally defined as a variable to which multiple values are assigned simultaneously. For example, in the previous chapter you assigned a list of values to a single variable, Miles per gallon. This is an example of a simple one-dimensional array. When you defined Fuel cost using the Miles per gallon array variable as an input, it also became an array. This demonstrates the concept of array abstraction. Array variables can be used just like ordinary variables in expressions. Whenever you expand an index of the array to include more values, or even add an entirely new index along a new dimension, all dependent variables downstream will be extended automatically! Intelligent arrays allow you to scale your model without making any changes to the design.

This Chapter is rich in content and covers lots of ground. The example model is still somewhat simplified, but it is chosen to be complex enough to demonstrate as many important array concepts as possible. The workflow will be streamlined to allow you to concentrate on the ideas with-out getting bogged down with procedural details. Therefore, you should already be familiar with the basic mechanics of Analytica‘s user interface.

The prerequisite skills include:

• Creating a new model; Opening an existing model; Save; Save As... (See Chapter 1)
• Creating and defining new variables; Entering attributes in Attribute or Object windows; Drawing influence arrows between nodes. (See Chapter 4)

See Also

Tutorial Chapter 4 <-

Working with Arrays (Tables)

-> Creating the Party Problem Model