Numerical Methods for Estimating Loglet Parameters from Time-Series
Growth rates and the bell'' view
The Mathematics of Loglet Analysis

## Residuals

Residuals are the error, or difference, between the model and the observed data. The residual vector is defined by

The residual vector is plotted in Figure 5B.

We can also calculate residuals as percentage error:

It is crucial to examine the residuals after a fit. When a fit is good,'' the residuals are non-uniformly distributed around the zero axis; that is, they appear to be random in magnitude and sign. A substantial or systematic deviation from the zero axis indicates some phenomenon is not being modeled or fitted correctly. An iterative process of fitting loglets to a data set and then examining the residuals is a good way to proceed, unless the errors in the data and shown in the residuals are known to come from other sources (e.g., a recession).

Loglet Lab provides views of both percentage and raw error.

Perrin S Meyer
1998-07-14