Numerical Methods for Estimating Loglet Parameters from Time-Series

Growth rates and the ``bell'' view

The Mathematics of Loglet Analysis

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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*