[Read more...]

Data must be selected carefully.  The predictive usefulness of the model is grossly diminished if outliers taint the available data.  Figure 1, for instance, shows the Defense spending (as a fraction of the national budget) between 1948 and 1968. Note how the trend curve (as defined by our linear difference model from the ... [Read more...]

(This is the second of a series of ongoing posts on using Graph Algebra in the Social Sciences.) First-order linear difference equations are powerful, yet simple modeling tools.  They can provide access to useful substantive insights to real-world phenomena.  They can have powerful predictive ability when used appropriately.  Additionally, they ... [Read more...]

(This is the first in a series on the use of Graph Algebraic models for Social Science.) Linear Difference models are a hugely important first step in learning Graph Algebraic modeling.  That said, linear difference equations are a completely independent thing from Graph Algebra.  I’ll get into the Graph ... [Read more...]